Privacy Leakage and the Manipulation of Public Opinion in Online Social Networks

PRIVACY LEAKAGE AND THE MANIPULATION OF PUBLIC OPINION IN ONLINE SOCIAL NETWORKS Inauguraldissertation der Philosophisch-naturwissenschaftlichen Fakultät der Universität Bern vorgelegt von Luca Luceri von Italien Leiter der Arbeit: Professor Dr. Torsten Braun Institut für Informatik | downloaded: 11.10.2021 Professor Dr. Silvia Giordano University of Applied Sciences and Arts of Southern Switzerland Original document saved on the web server of the University Library of Bern This work is licensed under a Creative Commons Attribution-Non-Commercial-No derivative works 2.5 Switzerland licence. To see the licence go to http://creativecommons.org/licenses/by-nc-nd/2.5/ch/ or write to Creative Commons, 171 Second Street, Suite 300, San Francisco, California 94105, USA. https://doi.org/10.7892/boris.142613 source: PRIVACY LEAKAGE AND THE MANIPULATION OF PUBLIC OPINION IN ONLINE SOCIAL NETWORKS Inauguraldissertation der Philosophisch-naturwissenschaftlichen Fakultät der Universität Bern vorgelegt von Luca Luceri von Italien Leiter der Arbeit: Professor Dr. Torsten Braun Institut für Informatik Professor Dr. Silvia Giordano University of Applied Sciences and Arts of Southern Switzerland Von der Philosophisch-naturwissenschaftlichen Fakultät angenommen. Der Dekan: Bern, March 31, 2020 Prof. Dr. Zoltan Balogh Copyright Notice This document is licensed under the Creative Commons Attribution-Non-Commercial- No derivative works 2.5 Switzerland. http://creativecommons.org/licenses/by-nc- nd/2.5/ch/ You are free: to copy, distribute, display, and perform the work Under the following conditions: Attribution. You must give the original author credit. Non-Commercial. You may not use this work for commercial purposes. No derivative works. You may not alter, transform, or build upon this work. For any reuse or distribution, you must take clear to others the license terms of this work. Any of these conditions can be waived if you get permission from the copyright holder. Nothing in this license impairs or restricts the author’s moral rights according to Swiss law. The detailed license agreement can be found at: http://creativecommons.org/licenses/by-nc-nd/2.5/ch/legalcode.de Dedicated to my Family Acknowledgements The work here presented was carried out during my doctoral studies at the Univer- sity of Bern and the University of Applied Sciences and Arts of Southern Switzerland (SUPSI), whose collaboration, under the frame of the Swiss National Science Founda- tion (SNSF) project “SwissSenseSinergy”, allowed me to pursue a Ph.D.. Also, part of this work has been conducted at the Information Science Institute at the University of Southern California (USC). This thesis is the result of many years of work, during which I had the pleasure of meeting and collaborating with amazing researchers around the globe. This achievement would not have been possible without their cooperation and the support of many people to whom I would like to express my gratitude. First of all, I would like to sincerely thank my supervisors, Prof. Dr. Torsten Braun and Prof. Silvia Giordano, for giving me the opportunity to pursue a Ph.D., guiding me towards this achievement, and allowing me to follow my own ideas. In particular, I thank Prof. Braun for giving me the chance to join the Communications and Distributed Systems (CDS) group of the University of Bern, and for considering me in every stimulating activities he organized with his group, especially the amazing summer schools. I am also grateful for all the advice, ideas, and corrections he has given me, and which helped me in publishing my work and completing this thesis. The help he gave me to turn my intuitions into rigorous research has been of invaluable importance to me. I cannot quantify the support of Silvia during my doctoral studies, especially during my most difficult periods. I have to express my deep gratitude to her for giving me inestimable aid in every day of the arduous path of this insidious undertaking, even when I was not behaving correctly or performing at my best. Without the motivation she has given me and the daily encouragement during these years, the way towards the Ph.D. would have been much more difficult. I cannot forget to mention her vision i Acknowledgements and intuitions, which have been of huge impact on the outcome of this work. I greatly thank her also, and enormously, for gifting me the most wonderful experience of my life: I will always be grateful to her for my working period and experience in US. Besides my supervisors, my sincere gratitude also goes to Emilio Ferrara, for accepting me at the Information Science Institute at USC, without knowing me at all and just trusting his unfailing flair for good people. I have to thank him for all the (countless) things I have learned from him. He has been fundamental in broadening my horizons in research and in looking at problems from a different prospective. A big thanks goes to all my CDS colleagues, in particular Mostafa, Gaetano, Ali, Jose, and Eirini, for the proficient conversations and advice about the Ph.D. life. An enormous thanks goes to Daniela Schroth, who has always been ready to help me with all the administrative procedures, especially during the completion of my Ph.D. Many thanks also to my colleagues at SUPSI, Michela, Alessandro, Francesca, Daniele, Kamini, Steven, and Luigi, who were always there to discuss interesting ideas and propose interesting points of view. I would also take the opportunity to thank Roberto and Tiziano, for allowing me to pursue my Ph.D. without any pressure. A special mention goes to my life saver Felipe (and Anto). Among my SUPSI colleagues, I need to mention and thank Davide: My roommate, colleague, and friend (in a pure random order). I cannot summarize our personal and professional relationship in a sentence (another thesis would be needed for that!). The time spent at USC would not have been the same without Adam, Anna, Ashok, Diana, Emilio, Goran, and Palash. Thanks for the good conversations, the proficient collaboration, and for making my time at USC a wonderful experience. I would like to express my gratitude to the SNSF,which funded my doctoral studies with the projects “SwissSenseSinergy” and “Uprise-IoT”. I cannot forget to thank all my friends. In particular, Vito V.Ivana, Mauro, Nigo, Marika, Barron (and his sweet half C) you have been fundamental in the moments of need. I cannot quantify the support you gave me and the funny moments spent together. Enormous gratitude goes to my family in Milan: Michele and Virginia, Andrea and Elena, Pietro and Giwta, Marco, Mauro, Giulio, and Tommy, you have been the best company for the nights and dinners in Milan. Saretta and Babby, there are no words to express the help and support you gave me during these years. Also, I need to mention my small family in Los Angeles: Amy and Trevor, Maja and Goran, and Chicco thanks for every moment spent together. ii Acknowledgements Least but not last, I would like to thank my family for all their support. You have been the most important source of encouragement and inspiration during my whole life. Thanks for always sticking by my side, even in the most complicated times. Bern, March 31, 2020 Luca iii Abstract Online Social Networks (OSNs) are computer-based technologies that enable users to create content, share information, and establish social relationships in online platforms. The advent of OSNs have dramatically revolutionized the way we access the news, share opinion, make business and politics. Although the wide adoption of OSNs brought several positive effects, the combination of its technological and social aspects hides harmful effects for both the individual users and the entire society. Among the potential risks analyzed in the literature (e.g., security, health, etc.), in this thesis, we analyze the perils related to the privacy leakage and the manipulation of opinions in OSNs. In particular, we investigate the factors driving these perils, with the final objective of raising users’ awareness of the risks behind their online activities. We show how, for both the privacy and manipulation perils, social connections play a central role in fostering and exacerbating such issues. In fact, social connections among OSN users result in a network structure, which enables the spreading of information, behaviors, and opinions across the OSN population through online interactions. Along this research direction, we first explore to what extent an individual’s privacy can be violated by leveraging information provided by other users in the OSN. In particular, we examine the problem of location privacy by developing methods to assess users’ privacy risks and strategies to control the public exposure of their data. Then, we explore the privacy peril by considering the diffusion of behaviors and opinions in OSNs. In fact, social interactions can substantially affect the extent to which a behavior, an opinion, or a product is adopted by OSN users. This concept is a social phenomenon referred to as social influence. According to this concept, we investigate whether social influence modeling (i.e., learning influence strengths among subjects) can be used to accurately predict users’ future activity and, in turn, violate their privacy. We present different approaches to model social influence and we show how such models can be employed to violate users’ privacy. Online interactions and social influence play also a crucial role in the manipulation of v Acknowledgements peoples’ belief and opinion. Manipulation campaigns have raised particular concerns in the political context. Bots (i.e., software-controlled accounts) and trolls (i.e., state- sponsored human operators) are the main actors responsible for these campaigns. In this thesis, we analyze the activity of such malicious actors to enhance and enable countermeasures for their detection. More specifically, we first uncover the strategies employed by bots to avoid detection and manipulate human users.

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