Ian P. Swift
Abolfazl Asudeh
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Abstract
Content spread inequity is a potential unfairness issue in online social networks, disparately impacting minority groups. In this paper, we view friendship suggestion, a common feature in social network platforms, as an opportunity to achieve an equitable spread of content. In particular, we propose to suggest a subset of potential edges (currently not existing in the network but likely to be accepted) that maximizes content spread while achieving fairness. Instead of re-engineering the existing systems, our proposal builds a fairness wrapper on top of the existing friendship suggestion components.
We prove the problem is NP-hard and inapproximable in polynomial time unless P = NP. Therefore, allowing relaxation of the fairness constraint, we propose an algorithm based on LP-relaxation and randomized rounding with fixed approximation ratios on fairness and content spread. We provide multiple optimizations, further improving the performance of our algorithm in practice. Besides, we propose a scalable algorithm that dynamically adds subsets of nodes, chosen via iterative sampling, and solves smaller problems corresponding to these nodes. Besides theoretical analysis, we conduct comprehensive experiments on real and synthetic data sets. Across different settings, our algorithms found solutions with near-zero unfairness while significantly increasing the content spread. Our scalable algorithm could process a graph with half a million nodes on a single machine, reducing the unfairness to around 0.0004 while lifting content spread by 43%.
- Chiara Accinelli, Barbara Catania, Giovanna Guerrini, and Simone Minisi. 2021. The impact of rewriting on coverage constraint satisfaction.. In EDBT/ICDT Workshops.Google Scholar
- Eytan Adar and Lada A Adamic. 2005. Tracking information epidemics in blogspace. In WI. IEEE, 207--214.Google Scholar
- Abolfazl Asudeh, Tanya Berger-Wolf, Bhaskar DasGupta, and Anastasios Sidiropoulos. 2020. Maximizing coverage while ensuring fairness: a tale of conflicting objective. CoRR, abs/2007.08069 (2020).Google Scholar
- Abolfazl Asudeh and HV Jagadish. 2020. Fairly evaluating and scoring items in a data set. PVLDB 13, 12 (2020), 3445--3448.Google ScholarDigital Library
- Abolfazl Asudeh, HV Jagadish, Julia Stoyanovich, and Gautam Das. 2019. Designing fair ranking schemes. In SIMGOD. 1259--1276.Google Scholar
- Abolfazl Asudeh, Zhongjun Jin, and HV Jagadish. 2019. Assessing and remedying coverage for a given dataset. In ICDE. IEEE, 554--565.Google Scholar
- Abolfazl Asudeh, Nima Shahbazi, Zhongjun Jin, and HV Jagadish. 2021. Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes. In SIGMOD. 129--141.Google Scholar
- Suman Banerjee, Mamata Jenamani, and Dilip Kumar Pratihar. 2020. A survey on influence maximization in a social network. KAIS 62, 9 (2020), 3417--3455.Google ScholarDigital Library
- Solon Barocas, Moritz Hardt, and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org.Google Scholar
- Solon Barocas and Andrew D Selbst. 2016. Big data's disparate impact. Calif. L. Rev. 104 (2016), 671.Google Scholar
- Lori Beaman and Andrew Dillon. 2018. Diffusion of agricultural information within social networks: Evidence on gender inequalities from Mali. Journal of Development Economics 133 (2018), 147--161.Google ScholarCross Ref
- Ruben Becker, Gianlorenzo D'Angelo, Sajjad Ghobadi, and Hugo Gilbert. 2022. Fairness in influence maximization through randomization. Journal of Artificial Intelligence Research 73 (2022), 1251--1283.Google ScholarDigital Library
- Hannah Beilinson. 2020. Fairness and Information Access Clustering in Social Networks. Ph.D. Dissertation.Google Scholar
- David Bindel, Jon Kleinberg, and Sigal Oren. 2015. How bad is forming your own opinion? Games and Economic Behavior 92 (2015), 248--265.Google ScholarCross Ref
- Flavio Calmon, Dennis Wei, Bhanukiran Vinzamuri, Karthikeyan Natesan Ramamurthy, and Kush R Varshney. 2017. Optimized pre-processing for discrimination prevention. In NIPS. 3992--4001.Google ScholarDigital Library
- Massimiliano Caramia and Paolo Dell'Olmo. 2008. Multi-objective management in freight logistics. Springer.Google Scholar
- Dumitru-Clementin Cercel and Stefan Trausan-Matu. 2014. Opinion propagation in online social networks: A survey. In Proceedings of the 4th international conference on web intelligence, mining and semantics (WIMS14). 1--10.Google ScholarDigital Library
- Meeyoung Cha, Alan Mislove, and Krishna P Gummadi. 2009. A measurement-driven analysis of information propagation in the flickr social network. In Proceedings of the 18th international conference on World wide web. 721--730.Google ScholarDigital Library
- Vineet Chaoji, Sayan Ranu, Rajeev Rastogi, and Rushi Bhatt. 2012. Recommendations to boost content spread in social networks. In Proceedings of the 21st international conference on World Wide Web. 529--538.Google ScholarDigital Library
- Wei Chen, Chi Wang, and Yajun Wang. 2010. Scalable influence maximization for prevalent viral marketing in large-scale social networks. In KDD. 1029--1038.Google Scholar
- Xi Chen, Jefrey Lijffijt, and Tijl De Bie. 2018. Quantifying and minimizing risk of conflict in social networks. In KDD. 1197--1205.Google Scholar
- Uthsav Chitra and Christopher Musco. 2020. Analyzing the impact of filter bubbles on social network polarization. In WSDM. 115--123.Google Scholar
- Michael B Cohen, Yin Tat Lee, and Zhao Song. 2021. Solving linear programs in the current matrix multiplication time. JACM 68, 1 (2021), 1--39.Google ScholarDigital Library
- Thomas H Cormen, Charles E Leiserson, Ronald L Rivest, and Clifford Stein. 2022. Introduction to algorithms. MIT press.Google Scholar
- Pedro Domingos and Matt Richardson. 2001. Mining the network value of customers. In KDD. 57--66.Google Scholar
- Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. 2012. Fairness through awareness. In ITCS. 214--226.Google Scholar
- David Easley and Jon Kleinberg. 2010. Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge university press.Google ScholarDigital Library
- Alessandro Epasto, Silvio Lattanzi, Vahab Mirrokni, Ismail Oner Sebe, Ahmed Taei, and Sunita Verma. 2015. Ego-net community mining applied to friend suggestion. PVLDB 9, 4 (2015), 324--335.Google ScholarDigital Library
- Golnoosh Farnadi, Behrouz Babaki, and Michel Gendreau. 2020. A Unifying Framework for Fairness-Aware Influence Maximization. In Companion Proceedings of the Web Conference 2020 (Taipei, Taiwan) (WWW '20). Association for Computing Machinery, New York, NY, USA, 714--722. Google ScholarDigital Library
- Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. 2015. Certifying and removing disparate impact. In SIGKDD. 259--268.Google Scholar
- He Feng and Xueming Qian. 2013. Recommendation via user's personality and social contextual. In CIKM. 1521--1524.Google Scholar
- Benjamin Fish, Ashkan Bashardoust, Danah Boyd, Sorelle Friedler, Carlos Scheidegger, and Suresh Venkatasubramanian. 2019. Gaps in Information Access in Social Networks?. In WWW. 480--490.Google Scholar
- James H Fowler and Nicholas A Christakis. 2008. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. Bmj 337 (2008).Google Scholar
- Noah E Friedkin and Eugene C Johnsen. 1990. Social influence and opinions. Journal of Mathematical Sociology 15, 3--4 (1990), 193--206.Google ScholarCross Ref
- Sorelle A Friedler, Carlos Scheidegger, Suresh Venkatasubramanian, Sonam Choudhary, Evan P Hamilton, and Derek Roth. 2019. A comparative study of fairness-enhancing interventions in machine learning. In Proceedings of the conference on fairness, accountability, and transparency. 329--338.Google ScholarDigital Library
- Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R Varshney, Rachel Bellamy, Kuntal Dey, et al. 2022. Causal Feature Selection for Algorithmic Fairness. (2022).Google Scholar
- Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis. 2017. Reducing controversy by connecting opposing views. In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. 81--90.Google ScholarDigital Library
- Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis. 2018. Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. In Proceedings of the 2018 world wide web conference. 913--922.Google ScholarDigital Library
- Shay Gershtein, Tova Milo, Brit Youngmann, and Gal Zeevi. 2018. IM balanced: influence maximization under balance constraints. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 1919--1922.Google ScholarDigital Library
- Aristides Gionis, Evimaria Terzi, and Panayiotis Tsaparas. 2013. Opinion maximization in social networks. In Proceedings of the 2013 SIAM International Conference on Data Mining. SIAM, 387--395.Google ScholarCross Ref
- Daniel Gruhl, Ramanathan Guha, David Liben-Nowell, and Andrew Tomkins. 2004. Information diffusion through blogspace. In Proceedings of the 13th international conference on World Wide Web. 491--501.Google ScholarDigital Library
- Pedro Guerra, Wagner Meira Jr, Claire Cardie, and Robert Kleinberg. 2013. A measure of polarization on social media networks based on community boundaries. In AAAI, Vol. 7. 215--224.Google Scholar
- Evren Güney. 2019. An efficient linear programming based method for the influence maximization problem in social networks. Information Sciences 503 (2019), 589--605.Google ScholarDigital Library
- Md Hamid, Md Naser, Md Hasan, Hasan Mahmud, et al. 2014. A cohesion-based friend-recommendation system. Social Network Analysis and Mining 4, 1 (2014), 1--11.Google ScholarCross Ref
- Anikó Hannák, Claudia Wagner, David Garcia, Alan Mislove, Markus Strohmaier, and Christo Wilson. 2017. Bias in online freelance marketplaces: Evidence from taskrabbit and fiverr. In CSCW. 1914--1933.Google Scholar
- Moritz Hardt, Eric Price, and Nati Srebro. 2016. Equality of opportunity in supervised learning. Advances in neural information processing systems 29 (2016).Google Scholar
- Eduardo Hargreaves, Claudio Agosti, Daniel Menasché, Giovanni Neglia, Alexandre Reiffers-Masson, and Eitan Altman. 2019. Fairness in online social network timelines: Measurements, models and mechanism design. Performance Evaluation 129 (2019), 15--39.Google ScholarDigital Library
- Eduardo Martins Hargreaves and Daniel Sadoc Menasché. 2020. Filters for Social Media Timelines: Models, Biases, Fairness and Implications. In Anais Estendidos do XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. SBC, 153--160.Google Scholar
- Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou, and Babak Salimi. 2022. Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification. In Proceedings of the 2022 International Conference on Management of Data. 232--246.Google ScholarDigital Library
- Faisal Kamiran and Toon Calders. 2012. Data preprocessing techniques for classification without discrimination. Knowledge and Information Systems 33, 1 (2012), 1--33.Google ScholarDigital Library
- Faisal Kamiran, Toon Calders, and Mykola Pechenizkiy. 2010. Discrimination aware decision tree learning. In 2010 IEEE International Conference on Data Mining. IEEE, 869--874.Google ScholarDigital Library
- Toshihiro Kamishima, Shotaro Akaho, Hideki Asoh, and Jun Sakuma. 2012. Fairness-aware classifier with prejudice remover regularizer. In ECML PKDD. Springer, 35--50.Google Scholar
- Michael Kearns, Seth Neel, Aaron Roth, and Zhiwei Steven Wu. 2018. Preventing fairness gerrymandering: Auditing and learning for subgroup fairness. In ICML. 2564--2572.Google Scholar
- David Kempe, Jon Kleinberg, and Éva Tardos. 2003. Maximizing the spread of influence through a social network. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. 137--146.Google ScholarDigital Library
- Moein Khajehnejad, Ahmad Asgharian Rezaei, Mahmoudreza Babaei, Jessica Hoffmann, Mahdi Jalili, and Adrian Weller. 2021. Adversarial graph embeddings for fair influence maximization over social networks. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence. 4306--4312.Google Scholar
- Charlotte Laclau, Ievgen Redko, Manvi Choudhary, and Christine Largeron. 2021. All of the Fairness for Edge Prediction with Optimal Transport. In AISTATS. PMLR, 1774--1782.Google Scholar
- Kristina Lerman and Laurie Jones. 2006. Social browsing on flickr. CoRR, abs/0612047 (2006).Google Scholar
- Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. 2005. Graphs over time: densification laws, shrinking diameters and possible explanations. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining. 177--187.Google ScholarDigital Library
- Jure Leskovec and Andrej Krevl. 2014. SNAP Datasets: Stanford Large Network Dataset Collection. http://snap.stanford.edu/data.Google Scholar
- Yuchen Li, Ju Fan, Yanhao Wang, and Kian-Lee Tan. 2018. Influence maximization on social graphs: A survey. IEEE Transactions on Knowledge and Data Engineering 30, 10 (2018), 1852--1872.Google ScholarCross Ref
- Farzan Masrour, Tyler Wilson, Heng Yan, Pang-Ning Tan, and Abdol Esfahanian. 2020. Bursting the filter bubble: Fairness-aware network link prediction. In Proceedings of the AAAI conference on artificial intelligence, Vol. 34. 841--848.Google ScholarCross Ref
- Antonis Matakos, Evimaria Terzi, and Panayiotis Tsaparas. 2017. Measuring and moderating opinion polarization in social networks. Data Mining and Knowledge Discovery 31, 5 (2017), 1480--1505.Google ScholarDigital Library
- Rajeev Motwani and Prabhakar Raghavan. 1995. Randomized algorithms. Cambridge university press.Google ScholarDigital Library
- Cameron Musco, Christopher Musco, and Charalampos E Tsourakakis. 2018. Minimizing polarization and disagreement in social networks. In Proceedings of the 2018 World Wide Web Conference. 369--378.Google ScholarDigital Library
- Arvind Narayanan. 2018. Translation tutorial: 21 fairness definitions and their politics. In Proc. Conf. Fairness Accountability Transp., New York, USA, Vol. 1170. 3.Google Scholar
- Fatemeh Nargesian, Abolfazl Asudeh, and HV Jagadish. 2021. Tailoring Data Source Distributions for Fairness-aware Data Integration. PVLDB 14, 11 (2021).Google Scholar
- Fatemeh Nargesian, Abolfazl Asudeh, and HV Jagadish. 2022. Responsible Data Integration: Next-generation Challenges. In Proceedings of the 2022 International Conference on Management of Data. 2458--2464.Google ScholarDigital Library
- Alexandra Olteanu, Carlos Castillo, Fernando Diaz, and Emre Kiciman. 2019. Social data: Biases, methodological pitfalls, and ethical boundaries. Frontiers in Big Data 2 (2019), 13.Google ScholarCross Ref
- Alexandra Petri. 2020. Opinion: Let's make social media fair and balanced. The Washington Post.Google Scholar
- Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, and Milind Tambe. 2021. Fair influence maximization: A welfare optimization approach. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 35. 11630--11638.Google ScholarCross Ref
- Aida Rahmattalabi, Phebe Vayanos, Anthony Fulginiti, Eric Rice, Bryan Wilder, Amulya Yadav, and Milind Tambe. 2019. Exploring algorithmic fairness in robust graph covering problems. Advances in Neural Information Processing Systems 32 (2019).Google Scholar
- Praboda Rajapaksha, Reza Farahbakhsh, and Noël Crespi. 2017. Identifying content originator in social networks. In GLOBECOM 2017-2017 IEEE Global Communications Conference. IEEE, 1--6.Google ScholarDigital Library
- Matthew Richardson and Pedro Domingos. 2002. Mining knowledge-sharing sites for viral marketing. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining. 61--70.Google ScholarDigital Library
- Maayan Roth, Assaf Ben-David, David Deutscher, Guy Flysher, Ilan Horn, Ari Leichtberg, Naty Leiser, Yossi Matias, and Ron Merom. 2010. Suggesting friends using the implicit social graph. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining. 233--242.Google ScholarDigital Library
- Benedek Rozemberczki, Oliver Kiss, and Rik Sarkar. 2020. Little Ball of Fur: A Python Library for Graph Sampling. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM '20). ACM, 3133--3140.Google ScholarDigital Library
- Babak Salimi, Luke Rodriguez, Bill Howe, and Dan Suciu. 2019. Interventional fairness: Causal database repair for algorithmic fairness. In SIGMOD. 793--810.Google Scholar
- John Scott and Peter J Carrington. 2011. The SAGE handbook of social network analysis. SAGE publications.Google Scholar
- Nihar B Shah and Zachary Lipton. 2020. SIGMOD 2020 Tutorial on Fairness and Bias in Peer Review and Other Sociotechnical Intelligent Systems. In SIGMOD. 2637--2640.Google Scholar
- Nima Shahbazi, Yin Lin, Abolfazl Asudeh, and HV Jagadish. 2022. A Survey on Techniques for Identifying and Resolving Representation Bias in Data. CoRR, abs/2203.11852 (2022).Google Scholar
- Suraj Shetiya, Ian Swift, Abolfazl Asudeh, and Gautam Das. 2022. Fairness-Aware Range Queries for Selecting Unbiased Data. ICDE (2022).Google Scholar
- Nitai B Silva, Ren Tsang, George DC Cavalcanti, and Jyh Tsang. 2010. A graph-based friend recommendation system using genetic algorithm. In IEEE congress on evolutionary computation. IEEE, 1--7.Google Scholar
- Till Speicher, Muhammad Ali, Giridhari Venkatadri, Filipe Nunes Ribeiro, George Arvanitakis, Fabrício Benevenuto, Krishna P Gummadi, Patrick Loiseau, and Alan Mislove. 2018. Potential for discrimination in online targeted advertising. In ACM FAccT. PMLR, 5--19.Google Scholar
- Shani Starinsky. 2021. From Books to Facebook: How Social Media Became the Biggest Publisher of our Time. Publishing Research Quarterly (2021), 1--14.Google Scholar
- Julia Stoyanovich, Serge Abiteboul, Bill Howe, HV Jagadish, and Sebastian Schelter. 2022. Responsible data management. Commun. ACM 65, 6 (2022), 64--74.Google ScholarDigital Library
- Jiankai Sun, Deepak Ajwani, Patrick K Nicholson, Alessandra Sala, and Srinivasan Parthasarathy. 2017. Breaking cycles in noisy hierarchies. In Proceedings of the 2017 ACM on Web Science Conference. 151--160.Google ScholarDigital Library
- Ian P. Swift, Sana Ebhrahmi, Azade Nova, and Abolfazl Asudeh. 2022. Maximizing Fair Content Sperad via Edge Suggestion in Social Networks - Technical Report. CoRR, abs/2207.07704 (2022).Google Scholar
- Shaojie Tang, Jing Yuan, Xufei Mao, Xiang-Yang Li, Wei Chen, and Guojun Dai. 2011. Relationship classification in large scale online social networks and its impact on information propagation. In 2011 Proceedings IEEE INFOCOM. IEEE, 2291--2299.Google Scholar
- Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, and Yair Zick. 2019. Group-fairness in influence maximization. CoRR, abs/1903.00967 (2019).Google Scholar
- Zhibo Wang, Jilong Liao, Qing Cao, Hairong Qi, and Zhi Wang. 2014. Friendbook: a semantic-based friend recommendation system for social networks. IEEE transactions on mobile computing 14, 3 (2014), 538--551.Google Scholar
- Stanley Wasserman, Katherine Faust, et al. 1994. Social network analysis: Methods and applications. (1994).Google Scholar
- Dong Wei, Md Mouinul Islam, Baruch Schieber, and Senjuti Basu Roy. 2022. Rank Aggregation with Proportionate Fairness. In Proceedings of the 2022 International Conference on Management of Data. 262--275.Google ScholarDigital Library
- Blake Woodworth, Suriya Gunasekar, Mesrob I Ohannessian, and Nathan Srebro. 2017. Learning non-discriminatory predictors. In Conference on Learning Theory. PMLR, 1920--1953.Google Scholar
- Wenguo Yang, Jianmin Ma, Yi Li, Ruidong Yan, Jing Yuan, Weili Wu, and Deying Li. 2019. Marginal gains to maximize content spread in social networks. IEEE Transactions on Computational Social Systems 6, 3 (2019), 479--490.Google ScholarCross Ref
- Zahi K Yaseen and Yussef Marwan. 2016. The influence of social media on recruitment and selection process in SMEs. Journal of Small Business and Entrepreneurship Development 4, 2 (2016), 21--27.Google ScholarCross Ref
- Naohiro Yonemoto, Yoshitaka Kawashima, Kaori Endo, and Mitsuhiko Yamada. 2019. Gatekeeper training for suicidal behaviors: a systematic review. Journal of affective disorders 246 (2019), 506--514.Google ScholarCross Ref
- Ying Yu, Jinglan Jia, Deying Li, and Yuqing Zhu. 2017. Fair multi-influence maximization in competitive social networks. In WASA. Springer, 253--265.Google Scholar
- Zhi Yu, Can Wang, Jiajun Bu, Xin Wang, Yue Wu, and Chun Chen. 2015. Friend recommendation with content spread enhancement in social networks. Information Sciences 309 (2015), 102--118.Google ScholarDigital Library
- M. B. Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi. 2015. Fairness constraints: Mechanisms for fair classification. CoRR, abs/1507.05259 (2015).Google Scholar
- Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork. 2013. Learning fair representations. In International conference on machine learning. PMLR, 325--333.Google Scholar
- Hantian Zhang, Xu Chu, Abolfazl Asudeh, and Shamkant B Navathe. 2021. OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning. In SIGMOD. 2076--2088.Google Scholar
- Hantian Zhang, Nima Shahbazi, Xu Chu, and Abolfazl Asudeh. 2021. FairRover: explorative model building for fair and responsible machine learning. In Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning. 1--10.Google ScholarDigital Library
- Liwang Zhu, Qi Bao, and Zhongzhi Zhang. 2021. Minimizing Polarization and Disagreement in Social Networks via Link Recommendation. Advances in Neural Information Processing Systems 34 (2021).Google Scholar
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