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- research-articleMay 2024
FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering▪
Expert Systems with Applications: An International Journal (EXWA), Volume 242, Issue CMay 2024https://doi.org/10.1016/j.eswa.2023.122842AbstractActive Learning (AL) techniques have proven to be highly effective in reducing data labeling costs across a range of machine learning tasks. Nevertheless, one known challenge of these methods is their potential to introduce unfairness towards ...
Highlights- Presents a novel fairness-aware active learning method called FAL-CUR.
- FAL-CUR uses the proposed acquisition function and fair clustering for fairness.
- The acquisition function is defined using representative and uncertainty ...
- surveyApril 2024
FairSNA: Algorithmic Fairness in Social Network Analysis
ACM Computing Surveys (CSUR), Volume 56, Issue 8Article No.: 213, Pages 1–45https://doi.org/10.1145/3653711In recent years, designing fairness-aware methods has received much attention in various domains, including machine learning, natural language processing, and information retrieval. However, in social network analysis (SNA), designing fairness-aware ...
- research-articleMarch 2024
Mediating effects of NLP-based parameters on the readability of crowdsourced wikipedia articles
Applied Intelligence (KLU-APIN), Volume 54, Issue 5Mar 2024, Pages 4370–4391https://doi.org/10.1007/s10489-024-05399-wAbstractIn this era of information and communication technology, a large population relies on the Internet to gather information. One of the most popular information sources on the Internet is Wikipedia. Wikipedia is a free encyclopedia that provides a ...
- noteFebruary 2024
X-distribution: Retraceable Power-law Exponent of Complex Networks
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 5Article No.: 117, Pages 1–12https://doi.org/10.1145/3639413Network modeling has been explored extensively by means of theoretical analysis as well as numerical simulations for Network Reconstruction (NR). The network reconstruction problem requires the estimation of the power-law exponent (γ) of a given input ...
- ArticleNovember 2023
Privacy Lost in Online Education: Analysis of Web Tracking Evolution
Advanced Data Mining and ApplicationsAug 2023, Pages 440–455https://doi.org/10.1007/978-3-031-46664-9_30AbstractDigital tracking poses a significant and multifaceted threat to personal privacy and integrity. Tracking techniques, such as the use of cookies and scripts, are widespread on the World Wide Web and have become more pervasive in the past decade. ...
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- research-articleSeptember 2023
- research-articleMay 2023
Balanced and Unbalanced Triangle Count in Signed Networks
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 35, Issue 12Dec. 2023, Pages 12491–12496https://doi.org/10.1109/TKDE.2023.3272657Triangle count is a frequently used network statistic, possessing high computational cost. Moreover, this task gets even more complex in the case of signed networks which consist of unbalanced and balanced triangles. In this work, we propose a fast <bold>...
- ArticleFebruary 2023
Social Network Analysis of the Caste-Based Reservation System in India
Computational Data and Social Networks Dec 2022, Pages 203–214https://doi.org/10.1007/978-3-031-26303-3_18AbstractBeing as old as human civilization, discrimination based on various grounds such as race, creed, gender, and caste has existed for a long time. To undo the impact of this long-enduring historical discrimination, governments worldwide have adopted ...
- research-articleNovember 2022
HM-EIICT: Fairness-aware link prediction in complex networks using community information
Journal of Combinatorial Optimization (SPJCO), Volume 44, Issue 4Nov 2022, Pages 2853–2870https://doi.org/10.1007/s10878-021-00788-0AbstractThe evolution of online social networks is highly dependent on the recommended links. Most of the existing works focus on predicting intra-community links efficiently. However, it is equally important to predict inter-community links with high ...
- short-paperAugust 2022
A Bi-level Assessment of Twitter Data for Election Prediction: Delhi Assembly Elections 2020
WWW '22: Companion Proceedings of the Web Conference 2022April 2022, Pages 930–935https://doi.org/10.1145/3487553.3524673Elections are the backbone of any democratic country, where voters elect the candidates as their representatives. The emergence of social networking sites has provided a platform for political parties and their candidates to connect with voters in ...
- research-articleJuly 2022
Topic-based influential user detection: a survey
Applied Intelligence (KLU-APIN), Volume 53, Issue 5Mar 2023, Pages 5998–6024https://doi.org/10.1007/s10489-022-03831-7AbstractOnline Social networks have become an easy means of communication for users to share their opinion on various topics, including breaking news, public events, and products. The content posted by a user can influence or affect other users, and the ...
- short-paperJanuary 2022
The banking transactions dataset and its comparative analysis with scale-free networks
ASONAM '21: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningNovember 2021, Pages 283–296https://doi.org/10.1145/3487351.3488339We construct a network of 1.6 million nodes from banking transactions of users of Rabobank. We assign two weights on each edge, which are the aggregate transferred amount and the total number of transactions between the users from the year 2010 to 2020. ...
- ArticleNovember 2021
Community Detection Using Semilocal Topological Features and Label Propagation Algorithm
Computational Data and Social NetworksNov 2021, Pages 255–266https://doi.org/10.1007/978-3-030-91434-9_23AbstractThe detection of cohesive clusters with similar characteristics in multiple types of networks is of immense informational value to researchers. In this work, we propose a Weighted Semilocal Similarity based Label Propagation Algorithm (WSSLPA) for ...
- research-articleJune 2021
How Fair is Fairness-aware Representative Ranking?
WWW '21: Companion Proceedings of the Web Conference 2021April 2021, Pages 161–165https://doi.org/10.1145/3442442.3453458It has been observed in several works that the ranking of candidates based on their score can be biased for candidates belonging to the minority community. In recent works, the fairness-aware representative ranking was proposed for computing fairness-...
- ArticleDecember 2020
- research-articleApril 2020
Mitigating Misinformation in Online Social Network with Top-k Debunkers and Evolving User Opinions
WWW '20: Companion Proceedings of the Web Conference 2020April 2020, Pages 363–370https://doi.org/10.1145/3366424.3383297Online social networks provide an easy platform to share the information, and the spread of fake news and rumors has become prevalent, with severe consequences on major events including the US and Jakarta elections. Existing works have designed methods ...
- research-articleFebruary 2020
Discovering and leveraging communities in dark multi-layered networks for network disruption
ASONAM '18: Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningAugust 2018, Pages 1152–1159In this paper we introduce a methodology to identify communities in dark multilayered networks, taking into account that the main challenges of these networks are incompleteness, fuzzy boundaries, and dynamic behavior. To account for these ...
- research-articleJuly 2017
Three is The Answer: Combining Relationships to Analyze Multilayered Terrorist Networks
ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017July 2017, Pages 868–875https://doi.org/10.1145/3110025.3110154In this paper we introduce a methodology to create multilayered terrorist networks, taking into account that the main challenges of the data behind the networks are incompleteness, fuzzy boundaries, and dynamic behavior. To account for these dark ...
- research-articleJuly 2017
A Generative Model for the Layers of Terrorist Networks
ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017July 2017, Pages 690–697https://doi.org/10.1145/3110025.3110153Data about terrorist networks is sparse and not consistently tagged as desired for research. Moreover, such data collections are hard to come across, which makes it challenging to propose solutions for the dynamic phenomenon driving these networks. This ...
- short-paperJuly 2017
Fast Estimation of Closeness Centrality Ranking
ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017July 2017, Pages 80–85https://doi.org/10.1145/3110025.3110064Closeness centrality is one way of measuring how central a node is in the given network. The closeness centrality measure assigns a centrality value to each node based on its accessibility to the whole network. In real life applications, we are mainly ...