Publications (new)
2024
Jong, R. G.; Loo, M. P. J.; Takes, F. W.
The effect of distant connections on node anonymity in complex networks Journal Article
In: Scientific Reports, vol. 14, no. 1, pp. 1156, 2024, ISSN: 2045-2322.
Abstract | Links | BibTeX | Tags:
@article{de_jong_effect_2024,
title = {The effect of distant connections on node anonymity in complex networks},
author = {R. G. Jong and M. P. J. Loo and F. W. Takes},
url = {https://doi.org/10.1038/s41598-023-50617-z},
doi = {10.1038/s41598-023-50617-z},
issn = {2045-2322},
year = {2024},
date = {2024-01-01},
journal = {Scientific Reports},
volume = {14},
number = {1},
pages = {1156},
abstract = {Ensuring privacy of individuals is of paramount importance to social network analysis research. Previous work assessed anonymity in a network based on the non-uniqueness of a node’s ego network. In this work, we show that this approach does not adequately account for the strong de-anonymizing effect of distant connections. We first propose the use of d-k-anonymity, a novel measure that takes knowledge up to distance d of a considered node into account. Second, we introduce anonymity-cascade, which exploits the so-called infectiousness of uniqueness: mere information about being connected to another unique node can make a given node uniquely identifiable. These two approaches, together with relevant “twin node” processing steps in the underlying graph structure, offer practitioners flexible solutions, tunable in precision and computation time. This enables the assessment of anonymity in large-scale networks with up to millions of nodes and edges. Experiments on graph models and a wide range of real-world networks show drastic decreases in anonymity when connections at distance 2 are considered. Moreover, extending the knowledge beyond the ego network with just one extra link often already decreases overall anonymity by over 50%. These findings have important implications for privacy-aware sharing of sensitive network data.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sánchez-Olivares, E.; Boekhout, H. D.; Saxena, A.; Takes, F. W.
A Framework for Empirically Evaluating Pretrained Link Prediction Models Proceedings Article
In: Cherifi, H.; Rocha, L. M.; Cherifi, C.; Donduran, M. (Ed.): Complex Networks & Their Applications XII. Proceedings of the 12th International Conference on Complex Networks (Complex Networks 2023), pp. 150–161, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-53468-3.
Abstract | Links | BibTeX | Tags: Link Prediction, Pretrained Models, Transfer Learning
@inproceedings{sanchez_olivares_framework_2024,
title = {A Framework for Empirically Evaluating Pretrained Link Prediction Models},
author = {E. Sánchez-Olivares and H. D. Boekhout and A. Saxena and F. W. Takes},
editor = {H. Cherifi and L. M. Rocha and C. Cherifi and M. Donduran},
doi = {10.1007/978-3-031-53468-3_13},
isbn = {978-3-031-53468-3},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Complex Networks & Their Applications XII. Proceedings of the 12th International Conference on Complex Networks (Complex Networks 2023)},
pages = {150–161},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {This paper proposes a novel framework for empirically assessing the effect of network characteristics on the performance of pretrained link prediction models. In link prediction, the task is to predict missing or future links in a given network dataset. We focus on the pretrained setting, in which such a predictive model is trained on one dataset, and employed on another dataset. The framework allows one to overcome a number of nontrivial challenges in adequately testing the performance of such a pretrained model in a proper cross-validated setting. Experiments are performed on a corpus of 49 structurally diverse real-world complex network datasets from various domains with up to hundreds of thousands of nodes and edges. Overall results indicate that the extent to which a network is clustered is strongly related to whether this network is a suitable candidate to create a pretrained model on. Moreover, we systematically assessed the relationship between topological similarity and performance difference of pretrained models and a model trained on the same data. We find that similar network pairs in terms of clustering coefficient, and to a lesser extent degree assortativity and gini coefficient, yield minimal performance difference. The findings presented in this work pave the way for automated model selection based on topological similarity of the networks, as well as larger-scale deployment of pretrained link prediction models for transfer learning.},
keywords = {Link Prediction, Pretrained Models, Transfer Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
2023
Barata, A. P.; Takes, F. W.; Herik, H. J.; Veenman, C. J.
Fair tree classifier using strong demographic parity Journal Article
In: Machine Learning, 2023, ISSN: 1573-0565.
Abstract | Links | BibTeX | Tags: Criterion, Fairness, Sensitive, Society
@article{pereira_barata_fair_2023,
title = {Fair tree classifier using strong demographic parity},
author = {A. P. Barata and F. W. Takes and H. J. Herik and C. J. Veenman},
url = {https://doi.org/10.1007/s10994-023-06376-z},
doi = {10.1007/s10994-023-06376-z},
issn = {1573-0565},
year = {2023},
date = {2023-08-01},
urldate = {2023-08-01},
journal = {Machine Learning},
abstract = {When dealing with sensitive data in automated data-driven decision-making, an important concern is to learn predictors with high performance towards a class label, whilst minimising for the discrimination towards any sensitive attribute, like gender or race, induced from biased data. Hybrid tree optimisation criteria have been proposed which combine classification performance and fairness. Although the threshold-free ROC-AUC is the standard for measuring classification model performance, current fair tree classification methods mainly optimise for a fixed threshold on the fairness metric. In this paper, we propose SCAFF—splitting criterion AUC for Fairness—a compound decision tree splitting criterion which combines the threshold-free strong demographic parity with ROC-AUC termed, easily applicable as an ensemble. Our method simultaneously leverages multiple sensitive attributes of which the values may be multicategorical, and is tunable with respect to the unavoidable performance-fairness trade-off. In our experiments, we demonstrate how SCAFF generates effective models with competitive performance and fairness with respect to binary, multicategorical, and multiple sensitive attributes.},
keywords = {Criterion, Fairness, Sensitive, Society},
pubstate = {published},
tppubtype = {article}
}
Jong, R. G.; Loo, M. P. J.; Takes, F. W.
Algorithms for Efficiently Computing Structural Anonymity in Complex Networks Journal Article
In: ACM Journal of Experimental Algorithmics, vol. 28, pp. 1.7:1–1.7:22, 2023, ISSN: 1084-6654.
Abstract | Links | BibTeX | Tags: anonymity, Complex networks, graph algorithms, privacy
@article{de_jong_algorithms_2023,
title = {Algorithms for Efficiently Computing Structural Anonymity in Complex Networks},
author = {R. G. Jong and M. P. J. Loo and F. W. Takes},
url = {https://dl.acm.org/doi/10.1145/3604908},
doi = {10.1145/3604908},
issn = {1084-6654},
year = {2023},
date = {2023-08-01},
urldate = {2024-04-08},
journal = {ACM Journal of Experimental Algorithmics},
volume = {28},
pages = {1.7:1–1.7:22},
abstract = {This article proposes methods for efficiently computing the anonymity of entities in networks. We do so by partitioning nodes into equivalence classes where a node is k-anonymous if it is equivalent to k-1 other nodes. This assessment of anonymity is crucial when one wants to share data and must ensure the anonymity of entities represented is compliant with privacy laws. Additionally, in such an assessment, it is necessary to account for a realistic amount of information in the hands of a possible attacker that attempts to de-anonymize entities in the network. However, measures introduced in earlier work often assume a fixed amount of attacker knowledge. Therefore, in this work, we use a new parameterized measure for anonymity called d-k-anonymity. This measure can be used to model the scenario where an attacker has perfect knowledge of a node’s surroundings up to a given distance d. This poses nontrivial computational challenges, as naive approaches would employ large numbers of possibly computationally expensive graph isomorphism checks. This article proposes novel algorithms that severely reduce this computational burden. In particular, we present an iterative approach, assisted by techniques for preprocessing nodes that are trivially automorphic and heuristics that exploit graph invariants. We evaluate our algorithms on three well-known graph models and a wide range of empirical network datasets. Results show that our approaches significantly speed up the computation by multiple orders of magnitude, which allows one to compute d-k-anonymity for a range of meaningful values of d on large empirical networks with tens of thousands of nodes and over a million edges.},
keywords = {anonymity, Complex networks, graph algorithms, privacy},
pubstate = {published},
tppubtype = {article}
}
Bokányi, E.; Heemskerk, E. M.; Takes, F. W.
The anatomy of a population-scale social network Journal Article
In: Scientific Reports, vol. 13, no. 1, pp. 9209, 2023, ISSN: 2045-2322, (Publisher: Nature Publishing Group).
Abstract | Links | BibTeX | Tags: Complex networks, Socioeconomic scenarios
@article{bokanyi_anatomy_2023,
title = {The anatomy of a population-scale social network},
author = {E. Bokányi and E. M. Heemskerk and F. W. Takes},
url = {https://www.nature.com/articles/s41598-023-36324-9},
doi = {10.1038/s41598-023-36324-9},
issn = {2045-2322},
year = {2023},
date = {2023-06-01},
urldate = {2024-04-08},
journal = {Scientific Reports},
volume = {13},
number = {1},
pages = {9209},
abstract = {Large-scale human social network structure is typically inferred from digital trace samples of online social media platforms or mobile communication data. Instead, here we investigate the social network structure of a complete population, where people are connected by high-quality links sourced from administrative registers of family, household, work, school, and next-door neighbors. We examine this multilayer social opportunity structure through three common concepts in network analysis: degree, closure, and distance. Findings present how particular network layers contribute to presumably universal scale-free and small-world properties of networks. Furthermore, we suggest a novel measure of excess closure and apply this in a life-course perspective to show how the social opportunity structure of individuals varies along age, socio-economic status, and education level.},
note = {Publisher: Nature Publishing Group},
keywords = {Complex networks, Socioeconomic scenarios},
pubstate = {published},
tppubtype = {article}
}
Mattsson, C. E. S.; Criscione, T.; Takes, F. W.
Circulation of a digital community currency Journal Article
In: Scientific Reports, vol. 13, no. 1, pp. 5864, 2023, ISSN: 2045-2322, (Publisher: Nature Publishing Group).
Abstract | Links | BibTeX | Tags: Complex networks, Computational science
@article{mattsson_circulation_2023,
title = {Circulation of a digital community currency},
author = {C. E. S. Mattsson and T. Criscione and F. W. Takes},
url = {https://www.nature.com/articles/s41598-023-33184-1},
doi = {10.1038/s41598-023-33184-1},
issn = {2045-2322},
year = {2023},
date = {2023-04-01},
urldate = {2024-04-08},
journal = {Scientific Reports},
volume = {13},
number = {1},
pages = {5864},
abstract = {Circulation is the characteristic feature of successful currency systems, from community currencies to cryptocurrencies to national currencies. In this paper, we propose a network analysis approach especially suited for studying circulation given a system’s digital transaction records. Sarafu is a digital community currency that was active in Kenya over a period that saw considerable economic disruption due to the COVID-19 pandemic. We represent its circulation as a network of monetary flow among the 40,000 Sarafu users. Network flow analysis reveals that circulation was highly modular, geographically localized, and occurring among users with diverse livelihoods. Across localized sub-populations, network cycle analysis supports the intuitive notion that circulation requires cycles. Moreover, the sub-networks underlying circulation are consistently degree disassortative and we find evidence of preferential attachment. Community-based institutions often take on the role of local hubs, and network centrality measures confirm the importance of early adopters and of women’s participation. This work demonstrates that networks of monetary flow enable the study of circulation within currency systems at a striking level of detail, and our findings can be used to inform the development of community currencies in marginalized areas.},
note = {Publisher: Nature Publishing Group},
keywords = {Complex networks, Computational science},
pubstate = {published},
tppubtype = {article}
}
McNeil, M.; Mattsson, C. E. S.; Takes, F. W.; Bogdanov, P.
CADENCE: Community-Aware Detection of Dynamic Network States Proceedings Article
In: Proceedings of the 2023 SIAM International Conference on Data Mining (SDM), pp. 1–9, Society for Industrial and Applied Mathematics, 2023.
Abstract | Links | BibTeX | Tags:
@inproceedings{mcneil_cadence_2023,
title = {CADENCE: Community-Aware Detection of Dynamic Network States},
author = {M. McNeil and C. E. S. Mattsson and F. W. Takes and P. Bogdanov},
url = {https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch1},
doi = {10.1137/1.9781611977653.ch1},
year = {2023},
date = {2023-01-01},
urldate = {2024-04-08},
booktitle = {Proceedings of the 2023 SIAM International Conference on Data Mining (SDM)},
pages = {1–9},
publisher = {Society for Industrial and Applied Mathematics},
series = {Proceedings},
abstract = {Dynamic interaction data is often aggregated in a sequence of network snapshots before being employed in downstream analysis. The two common ways of defining network snapshots are i) a fixed time interval or ii) fixed number of interactions per snapshot. The choice of aggregation has a significant impact on subsequent analysis, and it is not trivial to select one approach over another for a given dataset. More importantly assuming snapshot regularity is data-agnostic and may be at odds with the underlying interaction dynamics.
To address these challenges, we propose a method for community-aware detection of network states (CADENCE) based on the premise of stable interaction time-frames within network communities. We simultaneously detect network communities and partition the global interaction activity into scale-adaptive snapshots where the level of interaction within communities remains stable. We model a temporal network as a node-node-time tensor and use a structured canonical polyadic decomposition with a piece-wise constant temporal factor to iteratively identify communities and their activity levels. We demonstrate that transitions between network snapshots learned by CADENCE constitute network change points of better quality than those predicted by state-of-the-art network change point detectors. Furthermore, the network structure within individual snapshots reflects ground truth communities better than baselines for adaptive tensor granularity. Through a case study on a real-world Reddit dataset, we showcase the interpretability of CADENCE motivated snapshots as periods separated by significant events.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
To address these challenges, we propose a method for community-aware detection of network states (CADENCE) based on the premise of stable interaction time-frames within network communities. We simultaneously detect network communities and partition the global interaction activity into scale-adaptive snapshots where the level of interaction within communities remains stable. We model a temporal network as a node-node-time tensor and use a structured canonical polyadic decomposition with a piece-wise constant temporal factor to iteratively identify communities and their activity levels. We demonstrate that transitions between network snapshots learned by CADENCE constitute network change points of better quality than those predicted by state-of-the-art network change point detectors. Furthermore, the network structure within individual snapshots reflects ground truth communities better than baselines for adaptive tensor granularity. Through a case study on a real-world Reddit dataset, we showcase the interpretability of CADENCE motivated snapshots as periods separated by significant events.
Boekhout, H. D.; Blokland, A. A. J.; Takes, F. W.
A large-scale longitudinal structured dataset of the dark web cryptomarket Evolution (2014-2015) Miscellaneous
2023, (_eprint: 2311.11878).
Abstract | Links | BibTeX | Tags:
@misc{boekhout_large-scale_2023,
title = {A large-scale longitudinal structured dataset of the dark web cryptomarket Evolution (2014-2015)},
author = {H. D. Boekhout and A. A. J. Blokland and F. W. Takes},
doi = {10.48550/arXiv.2311.11878},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
publisher = {arXiv},
abstract = {Dark Web Marketplaces (DWM) facilitate the online trade of illicit goods. Due to the illicit nature of these marketplaces, quality datasets are scarce and difficult to produce. The Dark Net Market archives (2015) presented raw scraped source files crawled from a selection of DWMs, including Evolution. Here, we present, specifically for the Evolution DWM, a structured dataset extracted from Dark Net Market archive data. Uniquely, many of the data quality issues inherent to crawled data are resolved. The dataset covers over 500 thousand forum posts and over 80 thousand listings, providing data on forums, topics, posts, forum users, market vendors, listings, and more. Additionally, we present temporal weighted communication networks extracted from this data. The presented dataset provides easy access to a high quality DWM dataset to facilitate the study of criminal behaviour and communication on such DWMs, which may provide a relevant source of knowledge for researchers across disciplines, from social science to law to network science.},
note = {_eprint: 2311.11878},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
Boekhout, H. D.; Blokland, A. A. J.; Takes, F. W.
Early warning signals for predicting cryptomarket vendor success using dark net forum networks Miscellaneous
arXiv 2306.16568, 2023, (_eprint: 2306.16568).
Abstract | Links | BibTeX | Tags:
@misc{boekhout_early_2023,
title = {Early warning signals for predicting cryptomarket vendor success using dark net forum networks},
author = {H. D. Boekhout and A. A. J. Blokland and F. W. Takes},
url = {https://doi.org/10.48550/arXiv.2306.16568},
doi = {10.48550/arXiv.2306.16568},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
publisher = {arXiv},
abstract = {In this work we focus on identifying key players in dark net cryptomarkets that facilitate online trade of illegal goods. Law enforcement aims to disrupt criminal activity conducted through these markets by targeting key players vital to the market's existence and success. We particularly focus on detecting successful vendors responsible for the majority of illegal trade. Our methodology aims to uncover whether the task of key player identification should center around plainly measuring user and forum activity, or that it requires leveraging specific patterns of user communication. We focus on a large-scale dataset from the Evolution cryptomarket, which we model as an evolving communication network. While user and forum activity measures are useful for identifying the most successful vendors, we find that betweenness centrality additionally identifies those with lesser activity in the network. But more importantly, analyzing the forum data over time, we find evidence that attaining a high betweenness score comes before vendor success. This suggests that the proposed network-driven approach of modelling user communication might prove useful as an early warning signal for key player identification.},
howpublished = {arXiv 2306.16568},
note = {_eprint: 2306.16568},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
2022
Fajardo, S.; Kleijn, J.; Takes, F. W.; Langejans, G. H. J.
Modelling and measuring complexity of traditional and ancient technologies using Petri nets Journal Article
In: PLOS ONE, vol. 17, no. 11, pp. e0278310, 2022, ISSN: 1932-6203, (Publisher: Public Library of Science).
Abstract | Links | BibTeX | Tags: Adhesives, Behavior, Coal, Graphs, Grasses, Latex, Procurement, Raw materials
@article{fajardo_modelling_2022,
title = {Modelling and measuring complexity of traditional and ancient technologies using Petri nets},
author = {S. Fajardo and J. Kleijn and F. W. Takes and G. H. J. Langejans},
url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278310},
doi = {10.1371/journal.pone.0278310},
issn = {1932-6203},
year = {2022},
date = {2022-11-01},
urldate = {2024-04-08},
journal = {PLOS ONE},
volume = {17},
number = {11},
pages = {e0278310},
abstract = {Technologies and their production systems are used by archaeologists and anthropologists to study complexity of socio-technical systems. However, there are several issues that hamper agreement about what constitutes complexity and how we can systematically compare the complexity of production systems. In this work, we propose a novel approach to assess the behavioural and structural complexity of production systems using Petri nets. Petri nets are well-known formal models commonly used in, for example, biological and business process modelling, as well as software engineering. The use of Petri nets overcomes several obstacles of current approaches in archaeology and anthropology, such as the incompatibility of the intrinsic sequential logic of the available methods with inherently non-sequential processes, and the inability to explicitly model activities and resources separately. We test the proposed Petri net modelling approach on two traditional production systems of adhesives made by Ju/’hoan makers from Nyae, Namibia from Ammocharis coranica and Ozoroa schinzii plants. We run simulations in which we assess the complexity of these two adhesive production systems in detail and show how Petri net dynamics reveal the structural and behavioural complexity of different production scenarios. We show that concurrency may be prevalent in the production system of adhesive technologies and discuss how changes in location during the process may serve to control the behavioural complexity of a production system. The approach presented in this paper paves the way for future systematic visualization, analysis, and comparison of ancient production systems, accounting for the inherent complex, concurrent, and action/resource-oriented aspects of such processes.},
note = {Publisher: Public Library of Science},
keywords = {Adhesives, Behavior, Coal, Graphs, Grasses, Latex, Procurement, Raw materials},
pubstate = {published},
tppubtype = {article}
}
Beule, F. De; Elia, S.; Garcia-Bernardo, J.; Heemskerk, E. M.; Jaklič, A.; Takes, F. W.; Zdziarski, M.
Proximity at a distance: The relationship between foreign subsidiary co-location and MNC headquarters board interlock formation Journal Article
In: International Business Review, vol. 31, no. 4, pp. 101971, 2022, ISSN: 0969-5931.
Abstract | Links | BibTeX | Tags: Board interlocks, HQ-subsidiary relations, Internationalization, Proximity, Resource dependence, Subsidiary co-location, Transnational board interlocks
@article{de_beule_proximity_2022,
title = {Proximity at a distance: The relationship between foreign subsidiary co-location and MNC headquarters board interlock formation},
author = {F. De Beule and S. Elia and J. Garcia-Bernardo and E. M. Heemskerk and A. Jaklič and F. W. Takes and M. Zdziarski},
url = {https://www.sciencedirect.com/science/article/pii/S096959312100189X},
doi = {10.1016/j.ibusrev.2021.101971},
issn = {0969-5931},
year = {2022},
date = {2022-08-01},
urldate = {2024-04-08},
journal = {International Business Review},
volume = {31},
number = {4},
pages = {101971},
abstract = {Corporations seek various relationships, such as board interlocks, with other firms to reduce resource dependencies. The consistent theoretical expectation and empirical finding that physical proximity is an important driver for board interlock formation is seemingly at odds with the emerging and growing literature on transnational board interlock ties. We argue that the effect of proximity on multinational corporation (MNC) board interlock formation can also be attributed to the firms’ internationalization strategy, namely, when they have co-located subsidiaries in foreign markets. We call this “proximity at a distance”. We test our assumptions on a dataset covering almost 43,000 board interlocks among MNC headquarters and their 12 million subsidiary co-location pairs. We confirm that proximity among headquarters increases the odds of interlocking but also find robust evidence that co-located subsidiaries also increase firms’ propensity to interlock, particularly for transnational board interlocks. Our results help provide an explanation for the “paradox of distance” by showing that the interlock between two distant MNCs may be driven by proximity to their foreign subsidiaries. As such, we illustrate how MNCs’ resource-dependent strategic responses can occur at the headquarters level to address uncertainties experienced at the subsidiary level.},
keywords = {Board interlocks, HQ-subsidiary relations, Internationalization, Proximity, Resource dependence, Subsidiary co-location, Transnational board interlocks},
pubstate = {published},
tppubtype = {article}
}
Nadiri, Amirhossein; Takes, F. W.
A Large-scale Temporal Analysis of User Lifespan Durability on the Reddit Social Media Platform Proceedings Article
In: Companion Proceedings of the Web Conference 2022, pp. 677–685, Association for Computing Machinery, New York, NY, USA, 2022, ISBN: 978-1-4503-9130-6.
Abstract | Links | BibTeX | Tags: Reddit, social network analysis, temporal social networks, user behavior, user career
@inproceedings{nadiri_large-scale_2022,
title = {A Large-scale Temporal Analysis of User Lifespan Durability on the Reddit Social Media Platform},
author = {Amirhossein Nadiri and F. W. Takes},
url = {https://dl.acm.org/doi/10.1145/3487553.3524699},
doi = {10.1145/3487553.3524699},
isbn = {978-1-4503-9130-6},
year = {2022},
date = {2022-08-01},
urldate = {2024-04-08},
booktitle = {Companion Proceedings of the Web Conference 2022},
pages = {677–685},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {WWW '22},
abstract = {Social media platforms thrive upon the intertwined combination of user-created content and social interaction between these users. In this paper, we aim to understand what early user activity patterns fuel an ultimately durable user lifespan. We do so by analyzing what behavior causes potentially durable contributors to abandon their “social career” at an early stage, despite a strong start. We use a uniquely processed temporal dataset of over 6 billion Reddit user interactions on covering over 14 years, which we make available together with this paper. The temporal data allows us to assess both user content creation activity and the way in which this content is perceived. We do so in three dimensions, being a user’s content a) engagement and perception, b) diversification, and c) contribution. Our experiments reveal that users who leave the platform quickly may initially receive good feedback on their posts, but in time experience a decrease in the perceived quality of their content. Concerning diversification, we find that early departing users focus on fewer content categories in total, but do “jump” between those content categories more frequently, perhaps in an (unsuccessful) search for recognition or a sense of belonging. Third, we see that users who stay with the platform for a more extended period gradually start contributing, whereas early departing users post their first comments relatively quickly. The findings from this paper may prove crucial for better understanding how social media platforms can in an early stage improve the overall user experience and feeling of belonging within the social ecosystem of the platform.},
keywords = {Reddit, social network analysis, temporal social networks, user behavior, user career},
pubstate = {published},
tppubtype = {inproceedings}
}
Brinkmann, G. G.; Rietveld, K. F. D.; Verbeek, F. J.; Takes, F. W.
Real-time interactive visualization of large networks on a tiled display system Journal Article
In: Displays, vol. 73, pp. 102164, 2022, ISSN: 0141-9382.
Abstract | Links | BibTeX | Tags: CUDA, GPU, Interactive visualization, Network visualization, Tiled display systems
@article{brinkmann_real-time_2022,
title = {Real-time interactive visualization of large networks on a tiled display system},
author = {G. G. Brinkmann and K. F. D. Rietveld and F. J. Verbeek and F. W. Takes},
url = {https://www.sciencedirect.com/science/article/pii/S0141938222000130},
doi = {10.1016/j.displa.2022.102164},
issn = {0141-9382},
year = {2022},
date = {2022-07-01},
urldate = {2024-04-08},
journal = {Displays},
volume = {73},
pages = {102164},
abstract = {This paper introduces a methodology for visualizing large real-world (social) network data on a high-resolution tiled display system. Advances in network drawing algorithms enabled real-time visualization and interactive exploration of large real-world networks. However, visualization on a typical desktop monitor remains challenging due to the limited amount of screen space and ever increasing size of real-world datasets. To solve this problem, we propose an integrated approach that employs state-of-the-art network visualization algorithms on a tiled display system consisting of multiple screens. Key to our approach is to use the machine’s graphics processing units (GPUs) to their fullest extent, in order to ensure an interactive setting with real-time visualization. To realize this, we extended a recent GPU-based implementation of a force-directed graph layout algorithm to multiple GPUs and combined this with a distributed rendering approach in which each graphics card in the tiled display system renders precisely the part of the network to be displayed on the monitors attached to it. Our evaluation of the approach on a 12-screen 25 megapixels tiled display system with three GPUs, demonstrates interactive performance at 60 frames per second for real-world networks with tens of thousands of nodes and edges. This constitutes a performance improvement of approximately 4 times over a single GPU implementation. All the software developed to implement our tiled visualization approach, including the multi-GPU network layout, rendering, display and interaction components, are made available as open-source software.},
keywords = {CUDA, GPU, Interactive visualization, Network visualization, Tiled display systems},
pubstate = {published},
tppubtype = {article}
}
van Kuppevelt, D. E.; Bakhshi, R.; Heemskerk, E. M.; Takes, F. W.
Community membership consistency applied to corporate board interlock networks Journal Article
In: Journal of Computational Social Science, vol. 5, no. 1, pp. 841–860, 2022, ISSN: 2432-2725.
Abstract | Links | BibTeX | Tags: Board interlocks, Community detection, Interlocking directorates, Modularity, Network analysis
@article{kuppevelt_community_2022,
title = {Community membership consistency applied to corporate board interlock networks},
author = {D. E. van Kuppevelt and R. Bakhshi and E. M. Heemskerk and F. W. Takes},
url = {https://doi.org/10.1007/s42001-021-00145-5},
doi = {10.1007/s42001-021-00145-5},
issn = {2432-2725},
year = {2022},
date = {2022-05-01},
urldate = {2024-04-08},
journal = {Journal of Computational Social Science},
volume = {5},
number = {1},
pages = {841–860},
abstract = {Community detection is a well-established method for studying the meso-scale structure of social networks. Applying a community detection algorithm results in a division of a network into communities that is often used to inspect and reason about community membership of specific nodes. This micro-level interpretation step of community structure is a crucial step in typical social science research. However, the methodological caveat in this step is that virtually all modern community detection methods are non-deterministic and based on randomization and approximated results. This needs to be explicitly taken into consideration when reasoning about community membership of individual nodes. To do so, we propose a metric of community membership consistency, that provides node-level insights in how reliable the placement of that node into a community really is. In addition, it enables us to distinguish the community core members of a community. The usefulness of the proposed metrics is demonstrated on corporate board interlock networks, in which weighted links represent shared senior level directors between firms. Results suggest that the community structure of global business groups is centered around persistent communities consisting of core countries tied by geographical and cultural proximity. In addition, we identify fringe countries that appear to associate with a number of different global business communities.},
keywords = {Board interlocks, Community detection, Interlocking directorates, Modularity, Network analysis},
pubstate = {published},
tppubtype = {article}
}
Bruin, G. J.; Barata, A. P.; Herik, H. J.; Takes, F. W.; Veenman, C. J.
Fair automated assessment of noncompliance in cargo ship networks Journal Article
In: EPJ Data Sci., vol. 11, no. 1, pp. 13, 2022.
@article{de_bruin_g_j_fair_2022,
title = {Fair automated assessment of noncompliance in cargo ship networks},
author = {G. J. Bruin and A. P. Barata and H. J. Herik and F. W. Takes and C. J. Veenman},
url = {https://doi.org/10.1140/epjds/s13688-022-00326-w},
doi = {10.1140/epjds/s13688-022-00326-w},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {EPJ Data Sci.},
volume = {11},
number = {1},
pages = {13},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Meertens, Q. A.; Diks, C. G. H.; van den Herik, H. J.; Takes, F. W.
Improving the Output Quality of Official Statistics Based on Machine Learning Algorithms Journal Article
In: Journal of Official Statistics, vol. 38, no. 2, pp. 485–508, 2022, (_eprint: https://doi.org/10.2478/jos-2022-0023).
Abstract | Links | BibTeX | Tags:
@article{meertens_improving_2022,
title = {Improving the Output Quality of Official Statistics Based on Machine Learning Algorithms},
author = {Q. A. Meertens and C. G. H. Diks and H. J. van den Herik and F. W. Takes},
url = {https://doi.org/10.2478/jos-2022-0023},
doi = {10.2478/jos-2022-0023},
year = {2022},
date = {2022-01-01},
journal = {Journal of Official Statistics},
volume = {38},
number = {2},
pages = {485–508},
abstract = {National statistical institutes currently investigate how to improve the output quality of official statistics based on machine learning algorithms. A key issue is concept drift, that is, when the joint distribution of independent variables and a dependent (categorical) variable changes over time. Under concept drift, a statistical model requires regular updating to prevent it from becoming biased. However, updating a model asks for additional data, which are not always available. An alternative is to reduce the bias by means of bias correction methods. In the article, we focus on estimating the proportion (base rate) of a category of interest and we compare two popular bias correction methods: the misclassification estimator and the calibration estimator. For prior probability shift (a specific type of concept drift), we investigate the two methods analytically as well as numerically. Our analytical results are expressions for the bias and variance of both methods. As numerical result, we present a decision boundary for the relative performance of the two methods. Our results provide a better understanding of the effect of prior probability shift on output quality. Consequently, we may recommend a novel approach on how to use machine learning algorithms in the context of official statistics.},
note = {_eprint: https://doi.org/10.2478/jos-2022-0023},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Boekhout, H. D.; Heemskerk, E. M.; Takes, F. W.
Evolution of the World Stage of Global Science from a Scientific City Network Perspective Proceedings Article
In: Benito, R. M.; Cherifi, C.; Cherifi, Hocine; Moro, Esteban; Rocha, Luis M.; Sales-Pardo, Marta (Ed.): Complex Networks & Their Applications X, pp. 142–154, Springer International Publishing, Cham, 2022, ISBN: 978-3-030-93409-5.
Abstract | Links | BibTeX | Tags: City networks, Rank correlation, Scientific cities, Scientific co-authorship networks, Temporal networks
@inproceedings{boekhout_evolution_2022,
title = {Evolution of the World Stage of Global Science from a Scientific City Network Perspective},
author = {H. D. Boekhout and E. M. Heemskerk and F. W. Takes},
editor = {R. M. Benito and C. Cherifi and Hocine Cherifi and Esteban Moro and Luis M. Rocha and Marta Sales-Pardo},
doi = {10.1007/978-3-030-93409-5_13},
isbn = {978-3-030-93409-5},
year = {2022},
date = {2022-01-01},
booktitle = {Complex Networks & Their Applications X},
pages = {142–154},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {This paper investigates the stability and evolution of the world stage of global science at the city level by analyzing changes in co-authorship network centrality rankings over time. Driven by the problem that there exists no consensus in the literature on how the spatial unit “city” should be defined, we first propose a new approach to delineate so-called scientific cities. On a high-quality Web of Science dataset of 21.5 million publications over the period 2008–2020, we study changes in centrality rankings of subsequent 3-year time-slices of scientific city co-authorship networks at various levels of impact. We find that, over the years, the world stage of global science has become more stable. Additionally, by means of a comparison with degree respecting rewired networks we reveal how new co-authorships between authors from previously unconnected cities more often connect ‘close’ cities in the network periphery.},
keywords = {City networks, Rank correlation, Scientific cities, Scientific co-authorship networks, Temporal networks},
pubstate = {published},
tppubtype = {inproceedings}
}
Valeeva, D.; Takes, F. W.; Heemskerk, E. M.
Beaten paths towards the transnational corporate elite Journal Article
In: International Sociology, vol. 37, no. 1, pp. 97–123, 2022, ISSN: 0268-5809, (Publisher: SAGE Publications Ltd).
Abstract | Links | BibTeX | Tags:
@article{valeeva_beaten_2022,
title = {Beaten paths towards the transnational corporate elite},
author = {D. Valeeva and F. W. Takes and E. M. Heemskerk},
url = {https://doi.org/10.1177/02685809211051661},
doi = {10.1177/02685809211051661},
issn = {0268-5809},
year = {2022},
date = {2022-01-01},
urldate = {2024-04-08},
journal = {International Sociology},
volume = {37},
number = {1},
pages = {97–123},
abstract = {The transnationalization of economic activities has fundamentally altered the world. One of the consequences that has intrigued scholars is the formation of a transnational corporate elite. While the literature tends to focus on the topology of the transnational board interlock network, little is known about its driving mechanisms. This article asks the question: what are the trajectories that corporate elites follow in driving the expansion of this network? To answer this, the authors employ a novel approach that models the transnationalization of elites using their board appointment sequences. The findings show that there are six transnationalization trajectories corporate elites follow to expand the network. The authors argue that while the transnational elite network appears as a global social structure, its generating mechanisms are regionally organized. This corroborates earlier findings on the fragmentation of the global network of corporate control, but also provides insights into how this network was shaped over time.},
note = {Publisher: SAGE Publications Ltd},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
2021
Boekhout, H. D.; Traag, V. A.; Takes, F. W.
Investigating scientific mobility in co-authorship networks using multilayer temporal motifs Journal Article
In: Network Science, vol. 9, no. 3, pp. 354–386, 2021, ISSN: 2050-1242, 2050-1250.
Abstract | Links | BibTeX | Tags: co-authorship networks, concurrent edges, motif counting, multilayer temporal motifs, network motifs, scientific collaboration, scientific mobility
@article{boekhout_investigating_2021,
title = {Investigating scientific mobility in co-authorship networks using multilayer temporal motifs},
author = {H. D. Boekhout and V. A. Traag and F. W. Takes},
url = {https://www.cambridge.org/core/journals/network-science/article/investigating-scientific-mobility-in-coauthorship-networks-using-multilayer-temporal-motifs/4A8730DC440D7BE7EF4E6306AEE6ACBD#},
doi = {10.1017/nws.2021.12},
issn = {2050-1242, 2050-1250},
year = {2021},
date = {2021-09-01},
urldate = {2024-04-08},
journal = {Network Science},
volume = {9},
number = {3},
pages = {354–386},
abstract = {This paper introduces a framework for understanding complex temporal interaction patterns in large-scale scientific collaboration networks. In particular, we investigate how two key concepts in science studies, scientific collaboration and scientific mobility, are related and possibly differ between fields. We do so by analyzing multilayer temporal motifs: small recurring configurations of nodes and edges.Driven by the problem that many papers share the same publication year, we first provide a methodological contribution: an efficient counting algorithm for multilayer temporal motifs with concurrent edges. Next, we introduce a systematic categorization of the multilayer temporal motifs, such that each category reflects a pattern of behavior relevant to scientific collaboration and mobility. Here, a key question concerns the causal direction: does mobility lead to collaboration or vice versa? Applying this framework to scientific collaboration networks extracted from Web of Science (WoS) consisting of up to 7.7 million nodes (authors) and 94 million edges (collaborations), we find that international collaboration and international mobility reciprocally influence one another. Additionally, we find that Social sciences & Humanities (SSH) scholars co-author to a greater extent with authors at a distance, while Mathematics & Computer science (M&C) scholars tend to continue to collaborate within the established knowledge network and organization.},
keywords = {co-authorship networks, concurrent edges, motif counting, multilayer temporal motifs, network motifs, scientific collaboration, scientific mobility},
pubstate = {published},
tppubtype = {article}
}
Bruin, G. J.; Veenman, C. J.; Herik, H. J.; Takes, F. W.
Supervised temporal link prediction in large-scale real-world networks Journal Article
In: Social Network Analysis and Mining, vol. 11, no. 1, pp. 80, 2021, ISSN: 1869-5469.
Abstract | Links | BibTeX | Tags: Multigraphs, Network evolution, Supervised learning, Temporal link prediction, Temporal networks
@article{de_bruin_supervised_2021,
title = {Supervised temporal link prediction in large-scale real-world networks},
author = {G. J. Bruin and C. J. Veenman and H. J. Herik and F. W. Takes},
url = {https://doi.org/10.1007/s13278-021-00787-3},
doi = {10.1007/s13278-021-00787-3},
issn = {1869-5469},
year = {2021},
date = {2021-08-01},
urldate = {2024-04-08},
journal = {Social Network Analysis and Mining},
volume = {11},
number = {1},
pages = {80},
abstract = {Link prediction is a well-studied technique for inferring the missing edges between two nodes in some static representation of a network. In modern day social networks, the timestamps associated with each link can be used to predict future links between so-far unconnected nodes. In these so-called temporal networks, we speak of temporal link prediction. This paper presents a systematic investigation of supervised temporal link prediction on 26 temporal, structurally diverse, real-world networks ranging from thousands to a million nodes and links. We analyse the relation between global structural properties of each network and the obtained temporal link prediction performance, employing a set of well-established topological features commonly used in the link prediction literature. We report on four contributions. First, using temporal information, an improvement of prediction performance is observed. Second, our experiments show that degree disassortative networks perform better in temporal link prediction than assortative networks. Third, we present a new approach to investigate the distinction between networks modelling discrete events and networks modelling persistent relations. Unlike earlier work, our approach utilises information on all past events in a systematic way, resulting in substantially higher link prediction performance. Fourth, we report on the influence of the temporal activity of the node or the edge on the link prediction performance, and show that the performance differs depending on the considered network type. In the studied information networks, temporal information on the node appears most important. The findings in this paper demonstrate how link prediction can effectively be improved in temporal networks, explicitly taking into account the type of connectivity modelled by the temporal edge. More generally, the findings contribute to a better understanding of the mechanisms behind the evolution of networks.},
keywords = {Multigraphs, Network evolution, Supervised learning, Temporal link prediction, Temporal networks},
pubstate = {published},
tppubtype = {article}
}
Mattsson, C. E. S.; Takes, F. W.
Trajectories through temporal networks Journal Article
In: Applied Network Science, vol. 6, no. 1, pp. 35, 2021, ISSN: 2364-8228.
Abstract | Links | BibTeX | Tags: Association football, Mobile money, Payment systems, Process-driven, Soccer, Temporal networks, Time-respecting paths, Trajectories, Walk processes
@article{mattsson_trajectories_2021,
title = {Trajectories through temporal networks},
author = {C. E. S. Mattsson and F. W. Takes},
url = {https://doi.org/10.1007/s41109-021-00374-7},
doi = {10.1007/s41109-021-00374-7},
issn = {2364-8228},
year = {2021},
date = {2021-05-01},
urldate = {2024-04-08},
journal = {Applied Network Science},
volume = {6},
number = {1},
pages = {35},
abstract = {What do football passes and financial transactions have in common? Both are networked walk processes that we can observe, where records take the form of timestamped events that move something tangible from one node to another. Here we propose an approach to analyze this type of data that extracts the actual trajectories taken by the tangible items involved. The main advantage of analyzing the resulting trajectories compared to using, e.g., existing temporal network analysis techniques, is that sequential, temporal, and domain-specific aspects of the process are respected and retained. As a result, the approach lets us produce contextually-relevant insights. Demonstrating the usefulness of this technique, we consider passing play within association football matches (an unweighted process) and e-money transacted within a mobile money system (a weighted process). Proponents and providers of mobile money care to know how these systems are used—using trajectory extraction we find that 73% of e-money was used for stand-alone tasks and only 21.7% of account holders built up substantial savings at some point during a 6-month period. Coaches of football teams and sports analysts are interested in strategies of play that are advantageous. Trajectory extraction allows us to replicate classic results from sports science on data from the 2018 FIFA World Cup. Moreover, we are able to distinguish teams that consistently exhibited complex, multi-player dynamics of play during the 2017–2018 club season using ball passing trajectories, coincidentally identifying the winners of the five most competitive first-tier domestic leagues in Europe.},
keywords = {Association football, Mobile money, Payment systems, Process-driven, Soccer, Temporal networks, Time-respecting paths, Trajectories, Walk processes},
pubstate = {published},
tppubtype = {article}
}
Mattsson, C. E. S.; Takes, F. W.; Heemskerk, E. M.; Diks, C. G. H.; Buiten, G.; Faber, A.; Sloot, P. M. A.
Functional Structure in Production Networks Journal Article
In: Frontiers in Big Data, vol. 4, 2021, ISSN: 2624-909X, (Publisher: Frontiers).
Abstract | Links | BibTeX | Tags: Bipartivity, complextiy economics, Economic statistics, Functional Networks, Inter-firm networks, Production networks, Trade linkages
@article{mattsson_functional_2021,
title = {Functional Structure in Production Networks},
author = {C. E. S. Mattsson and F. W. Takes and E. M. Heemskerk and C. G. H. Diks and G. Buiten and A. Faber and P. M. A. Sloot},
url = {https://www.frontiersin.org/articles/10.3389/fdata.2021.666712},
doi = {10.3389/fdata.2021.666712},
issn = {2624-909X},
year = {2021},
date = {2021-05-01},
urldate = {2021-05-01},
journal = {Frontiers in Big Data},
volume = {4},
abstract = {Production networks are integral to economic dynamics, yet dis-aggregated network dataon inter-firm trade is rarely collected and often proprietary. Here we situate company-level production networks within a wider space of networks that are different in nature, but similar in local connectivity structure. Through this lens, we study a regional and a national network of inferred trade relationships reconstructed from Dutch national economic statistics and re-interpret prior empirical findings. We find that company-level production networks have so-called functional structure, as previously identified in protein-protein interaction (PPI) networks. Functional networks are distinctive in their over-representation of closed squares, which we quantify using an existing measure called spectral bipartivity. Shared local connectivity structure lets us ferry insights between domains. PPI networks are shaped by complementarity, rather than homophily, and we use multi-layer directed configuration models to show that this principle explains the emergence of functional structure in production networks. Companies are especially similar to their close competitors, not to their trading partners. Our findings have practical implications for the analysis of production networks and give us precise terms for the local structural features that may be key to understanding their routine function, failure, and growth.},
note = {Publisher: Frontiers},
keywords = {Bipartivity, complextiy economics, Economic statistics, Functional Networks, Inter-firm networks, Production networks, Trade linkages},
pubstate = {published},
tppubtype = {article}
}
Baratchi, M.; Cao, L.; Kosters, W. A.; Lijffijt, J.; Rijn, J. N.; Takes, F. W.
Springer International Publishing, 2021, ISBN: 978-3-030-76640-5.
@book{baratchi_artificial_2021,
title = {Artificial Intelligence and Machine Learning: 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19–20, 2020, Revised Selected Papers},
author = {M. Baratchi and L. Cao and W. A. Kosters and J. Lijffijt and J. N. Rijn and F. W. Takes},
url = {https://books.google.nl/books?id=624vEAAAQBAJ},
isbn = {978-3-030-76640-5},
year = {2021},
date = {2021-01-01},
publisher = {Springer International Publishing},
series = {Communications in Computer and Information Science},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
Bruin, G. J.; Veenman, C. J.; Herik, H. J.; Takes, F. W.
Experimental Evaluation of Train and Test Split Strategies in Link Prediction Proceedings Article
In: Benito, Rosa M.; Cherifi, C.; Cherifi, H.; Moro, E.; Rocha, L. M.; Sales-Pardo, M. (Ed.): Complex Networks & Their Applications IX, pp. 79–91, Springer International Publishing, Cham, 2021, ISBN: 978-3-030-65351-4.
Abstract | Links | BibTeX | Tags: Link Prediction, Machine learning, Performance estimation
@inproceedings{de_bruin_experimental_2021,
title = {Experimental Evaluation of Train and Test Split Strategies in Link Prediction},
author = {G. J. Bruin and C. J. Veenman and H. J. Herik and F. W. Takes},
editor = {Rosa M. Benito and C. Cherifi and H. Cherifi and E. Moro and L. M. Rocha and M. Sales-Pardo},
doi = {10.1007/978-3-030-65351-4_7},
isbn = {978-3-030-65351-4},
year = {2021},
date = {2021-01-01},
booktitle = {Complex Networks & Their Applications IX},
pages = {79–91},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In link prediction, the goal is to predict which links will appear in the future of an evolving network. To estimate the performance of these models in a supervised machine learning model, disjoint and independent train and test sets are needed. However, objects in a real-world network are inherently related to each other. Therefore, it is far from trivial to separate candidate links into these disjoint sets.},
keywords = {Link Prediction, Machine learning, Performance estimation},
pubstate = {published},
tppubtype = {inproceedings}
}
Loo, M. P. J.; Jong, R. G.; Takes, F. W.; Vries, M.; Wolf, P. P.
Structural uniqueness in networks Proceedings Article
In: Expert Meeting on Statistical Data Confidentiality, 2021.
BibTeX | Tags:
@inproceedings{van_der_loo_structural_2021,
title = {Structural uniqueness in networks},
author = {M. P. J. Loo and R. G. Jong and F. W. Takes and M. Vries and P. P. Wolf},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Expert Meeting on Statistical Data Confidentiality},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
2020
Armentano, M. G.; Bagheri, E.; Kiseleva, J.; Takes, F. W.
Foreword to the special issue on mining actionable insights from online user generated content Journal Article
In: Information Retrieval Journal, vol. 23, no. 5, pp. 473–474, 2020, ISSN: 1573-7659.
@article{armentano_foreword_2020,
title = {Foreword to the special issue on mining actionable insights from online user generated content},
author = {M. G. Armentano and E. Bagheri and J. Kiseleva and F. W. Takes},
url = {https://doi.org/10.1007/s10791-020-09380-2},
doi = {10.1007/s10791-020-09380-2},
issn = {1573-7659},
year = {2020},
date = {2020-10-01},
urldate = {2024-04-08},
journal = {Information Retrieval Journal},
volume = {23},
number = {5},
pages = {473–474},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Valeeva, D.; Heemskerk, E. M.; Takes, F. W.
The duality of firms and directors in board interlock networks: A relational event modeling approach Journal Article
In: Social Networks, vol. 62, pp. 68–79, 2020, ISSN: 0378-8733.
Abstract | Links | BibTeX | Tags: Corporate networks, Elites, Interlocking directorates, Relational event modeling
@article{valeeva_duality_2020,
title = {The duality of firms and directors in board interlock networks: A relational event modeling approach},
author = {D. Valeeva and E. M. Heemskerk and F. W. Takes},
url = {https://www.sciencedirect.com/science/article/pii/S0378873320300186},
doi = {10.1016/j.socnet.2020.02.009},
issn = {0378-8733},
year = {2020},
date = {2020-07-01},
urldate = {2024-04-08},
journal = {Social Networks},
volume = {62},
pages = {68–79},
abstract = {The long tradition of scholarly work on corporate interlocks has left us with competing theoretical frameworks on the causes of interlock networks. Board interlocks are studied either as means to overcome the resource dependence of corporations or as a group cohesion mechanism of business elites. This contrast is due to an empirical divide of the literature where either the firms or the individuals are considered as decision-making bodies. In systematically ignoring the agency of the other group of actors, these literatures suffer from both theoretical and empirical biases in understanding the drivers of new interlocks. In this paper, we employ a relational event modeling technique that allows us to overcome this problem. The analysis of board appointments in Denmark demonstrates how in fact both personal and corporate considerations simultaneously drive the evolution of the corporate networks. The study of the duality of actors is essential for understanding the causes and consequences of corporate networks across time and space.},
keywords = {Corporate networks, Elites, Interlocking directorates, Relational event modeling},
pubstate = {published},
tppubtype = {article}
}
Armentano, M. G.; Bagheri, E.; Takes, F. W.; Yannibelli, V. D.
Foreword to the special issue on mining actionable insights from social networks Journal Article
In: Information Processing & Management, vol. 57, no. 2, pp. 102171, 2020, ISSN: 0306-4573.
@article{armentano_foreword_2020-1,
title = {Foreword to the special issue on mining actionable insights from social networks},
author = {M. G. Armentano and E. Bagheri and F. W. Takes and V. D. Yannibelli},
url = {https://www.sciencedirect.com/science/article/pii/S0306457319313111},
doi = {10.1016/j.ipm.2019.102171},
issn = {0306-4573},
year = {2020},
date = {2020-03-01},
urldate = {2024-04-08},
journal = {Information Processing & Management},
volume = {57},
number = {2},
pages = {102171},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Angenent, M. N.; Barata, A. P.; Takes, F. W.
Large-scale machine learning for business sector prediction Proceedings Article
In: Proceedings of the 35th Annual ACM Symposium on Applied Computing, pp. 1143–1146, Association for Computing Machinery, New York, NY, USA, 2020, ISBN: 978-1-4503-6866-7.
Abstract | Links | BibTeX | Tags: business sector prediction, data mining, explainable machine learning, financial statements
@inproceedings{angenent_large-scale_2020,
title = {Large-scale machine learning for business sector prediction},
author = {M. N. Angenent and A. P. Barata and F. W. Takes},
url = {https://dl.acm.org/doi/10.1145/3341105.3374084},
doi = {10.1145/3341105.3374084},
isbn = {978-1-4503-6866-7},
year = {2020},
date = {2020-03-01},
urldate = {2024-04-08},
booktitle = {Proceedings of the 35th Annual ACM Symposium on Applied Computing},
pages = {1143–1146},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {SAC '20},
abstract = {In this study we use machine learning to perform explainable business sector prediction from financial statements. Financial statements are a valuable source of information on the financial state and performance of firms. Recently, large-scale data on financial statements has become available in the form of open data sets. Previous work on such data mainly focused on predicting fraud and bankruptcy. In this paper we devise a model for business sector prediction, which has several valuable applications, including automated error and fraud detection. In addition, such a predictive model may help in completing similar datasets with missing sector information. The proposed method employs a supervised learning approach based on random forests that addresses business sector prediction as a classification task. Using a dataset from the Netherlands Chamber of Commerce, containing over 1.5 million financial statements from Dutch companies, we created an adequately-performing model for business sector prediction. By assessing which features are instrumental in the final classification model, we found that a small number of attributes is crucial for predicting the majority of business sectors. Interestingly, in some cases the presence or absence of a feature was more important than the value itself. The resulting insights may also prove useful in accounting, where the relation between financial statements and characteristics of the company is a frequently studied topic.},
keywords = {business sector prediction, data mining, explainable machine learning, financial statements},
pubstate = {published},
tppubtype = {inproceedings}
}
Duijn, M.; Preuss, M.; Spaiser, V.; Takes, F. W.; Verberne, S.
Springer International Publishing, 2020, ISBN: 978-3-030-61841-4.
@book{van_duijn_disinformation_2020,
title = {Disinformation in Open Online Media: Second Multidisciplinary International Symposium, MISDOOM 2020, Leiden, The Netherlands, October 26–27, 2020, Proceedings},
author = {M. Duijn and M. Preuss and V. Spaiser and F. W. Takes and S. Verberne},
url = {https://doi.org/10.1007/978-3-030-61841-4},
isbn = {978-3-030-61841-4},
year = {2020},
date = {2020-01-01},
publisher = {Springer International Publishing},
series = {Lecture Notes in Computer Science},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
Barbouch, M.; Takes, F. W.; Verberne, S.
Combining Language Models and Network Features for Relevance-Based Tweet Classification Proceedings Article
In: Aref, S.; Bontcheva, K.; Braghieri, M.; Dignum, F.; Giannotti, F.; Grisolia, F.; Pedreschi, D. (Ed.): Social Informatics, pp. 15–27, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-60975-7.
Abstract | Links | BibTeX | Tags:
@inproceedings{barbouch_combining_2020,
title = {Combining Language Models and Network Features for Relevance-Based Tweet Classification},
author = {M. Barbouch and F. W. Takes and S. Verberne},
editor = {S. Aref and K. Bontcheva and M. Braghieri and F. Dignum and F. Giannotti and F. Grisolia and D. Pedreschi},
doi = {10.1007/978-3-030-60975-7_2},
isbn = {978-3-030-60975-7},
year = {2020},
date = {2020-01-01},
booktitle = {Social Informatics},
pages = {15–27},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In this paper we present methods for categorizing Twitter data from eight natural disasters into topical classes. Automatically categorizing social media content is of great importance to crisis management organizations that must quickly identify relevant information during situations such as floodings and earthquakes. Unique to our approach is that we leverage both the content of the tweets and the influence of the users producing this content. We compare the effectiveness of traditional text classifiers to a transfer learning method with a large pre-trained language model (BERT). To understand user influence, the rank of the user in the underlying Twitter mention network is included in the classification process. The final approach consists of an ensemble of the best content-based model as well as various user rank features. We find that BERT outperforms traditional text classifiers, in particular for the larger categories. In addition, we find that the influence of a user based on his or her social position, is of high relevance in some particular tweet categories. The proposed approach may prove useful in the automated real-time detection of relevant Twitter content in crisis situations.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Duijn, M.; Preuss, M.; Spaiser, V.; Takes, F. W.; Verberne, S.
Correction to: Disinformation in Open Online Media Proceedings Article
In: Duijn, M.; Preuss, M.; Spaiser, V.; Takes, F. W.; Verberne, S. (Ed.): Disinformation in Open Online Media, pp. C1–C1, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-61841-4.
Abstract | Links | BibTeX | Tags:
@inproceedings{van_duijn_correction_2020,
title = {Correction to: Disinformation in Open Online Media},
author = {M. Duijn and M. Preuss and V. Spaiser and F. W. Takes and S. Verberne},
editor = {M. Duijn and M. Preuss and V. Spaiser and F. W. Takes and S. Verberne},
doi = {10.1007/978-3-030-61841-4_19},
isbn = {978-3-030-61841-4},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
booktitle = {Disinformation in Open Online Media},
pages = {C1–C1},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {In the original online version of the chapter 5 was previously published non-open access. It was changed to open access retrospectively under a CC BY 4.0 license and, the presentation of Table 3 was different to that of Tables 2 and 4. This has been corrected. In addition, Tables 5 - 8 have been moved from the main text to Appendix B, at the request of the authors.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Bruin, G. J.; Veenman, C. J.; Herik, H. J.; Takes, F. W.
Understanding Dynamics of Truck Co-Driving Networks Proceedings Article
In: Cherifi, H.; Gaito, S.; Mendes, J. F.; Moro, E.; Rocha, L. M. (Ed.): Complex Networks and Their Applications VIII, pp. 140–151, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-36683-4.
Abstract | Links | BibTeX | Tags: Co-driving behaviour, Link Prediction, Mobility, Spatio-temporal networks, Transport networks
@inproceedings{de_bruin_understanding_2020,
title = {Understanding Dynamics of Truck Co-Driving Networks},
author = {G. J. Bruin and C. J. Veenman and H. J. Herik and F. W. Takes},
editor = {H. Cherifi and S. Gaito and J. F. Mendes and E. Moro and L. M. Rocha},
doi = {10.1007/978-3-030-36683-4_12},
isbn = {978-3-030-36683-4},
year = {2020},
date = {2020-01-01},
booktitle = {Complex Networks and Their Applications VIII},
pages = {140–151},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {The goal of this paper is to learn the dynamics of truck co-driving behaviour. Understanding this behaviour is important because co-driving has a potential positive impact on the environment. In the so-called co-driving network, trucks are nodes while links indicate that two trucks frequently drive together. To understand the network’s dynamics, we use a link prediction approach employing a machine learning classifier. The features of the classifier can be categorized into spatio-temporal features, neighbourhood features, path features, and node features. The very different types of features allow us to understand the social processes underlying the co-driving behaviour. Our work is based on a spatio-temporal data not studied before. Data is collected from 18 million truck movements in the Netherlands. We find that co-driving behaviour is best described by using neighbourhood features, and to lesser extent by path and spatio-temporal features. Node features are deemed unimportant. Findings suggest that the dynamics of a truck co-driving network has clear social network effects.},
keywords = {Co-driving behaviour, Link Prediction, Mobility, Spatio-temporal networks, Transport networks},
pubstate = {published},
tppubtype = {inproceedings}
}
Meertens, Q. A.; Diks, C. G. H.; Herik, H. J.; Takes, F. W.
A Data-Driven Supply-Side Approach for Estimating Cross-Border Internet Purchases Within the European Union Journal Article
In: Journal of the Royal Statistical Society Series A: Statistics in Society, vol. 183, no. 1, pp. 61–90, 2020, ISSN: 0964-1998.
Abstract | Links | BibTeX | Tags:
@article{meertens_data-driven_2020,
title = {A Data-Driven Supply-Side Approach for Estimating Cross-Border Internet Purchases Within the European Union},
author = {Q. A. Meertens and C. G. H. Diks and H. J. Herik and F. W. Takes},
url = {https://doi.org/10.1111/rssa.12487},
doi = {10.1111/rssa.12487},
issn = {0964-1998},
year = {2020},
date = {2020-01-01},
urldate = {2024-04-08},
journal = {Journal of the Royal Statistical Society Series A: Statistics in Society},
volume = {183},
number = {1},
pages = {61–90},
abstract = {The digital economy is a highly relevant item on the European Union’s policy agenda. We focus on cross-border Internet purchases, as part of the digital economy, the total value of which cannot be accurately estimated by using existing consumer survey approaches. In fact, they lead to a serious underestimation. To obtain an accurate estimate, we propose a three-step data-driven approach based on supply-side data. For the first step, we develop a data-driven generic method for firm level probabilistic record linkage of tax data and business registers. In the second step, we use machine learning to identify webshops based on website data. Then, in the third step, we implement recently developed bias correction techniques that have hitherto been overlooked by the machine learning community. Subsequently, we claim that our three-step approach can be applied to any European Union member state, leading to more accurate estimates of cross-border Internet purchases than those obtained by currently existing approaches. To justify the claim, we apply our approach to the Netherlands for the year 2016 and find an estimate that is six times as high as current estimates, having a standard deviation of 8%. Hence, we may conclude that our new approach deserves more investigation and applications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}