Yotam Shmargad's CV
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Politics in Digital Society
Politics in Digital Society Ph.D. thesis by Troels Runge IT University at Copenhagen Submitted May 17, 2021 i Examination Committee Bente Kalsnes, Associate Professor, School of Communication, Leadership and Management, Kristiania University College, Norway Ulrike Klinger, Junior Professor, Institute for Media and Communication Studies, Freie University, Berlin, Germany. Gitte Stald, Associate Professor, IT University of Copenhagen, Head of Committee. Supervisors Lisbeth Klastrup, Associate Professor, IT University of Copenhagen. Luca Rossi, Associate Professor, IT University of Copenhagen. ii English Summary This thesis departs from the fact, that the use of social media platforms has become a precondition for politicians and parties, where social media have been presented as new opportunities to reach and engage voters, bypassing mass media, and levelling the political playing field. Now, however, politicians and parties face the limitations and control of platforms, and must submit to new forms of media logic, increased mediatization of politics. To comprehend this transformative shift, we must understand that digital and social media permeate all aspects of society, that we now live in a digital society. Sociologist Deborah Lupton have noted that “... the very idea of ‘culture’ or ‘society’ cannot now be fully understood without the recognition that computer software and hardware devices not only underpin but actively constitute selfhood, embodiment, social life, social relations and social institutions” (Lupton, 2014). This is certainly true in politics too. This thesis is contextualized within the formal arena of national politics in Denmark, including the Danish media system and the specificity of Danish political culture. Throughout the thesis, I focus on how social media platforms are used by Danish politicians, as an illustration of how the transformative power of platforms impacts formal politics, i.e., how politics is exercised and performed by politicians and political parties in election campaigns as well as in agenda-setting in everyday politics. -
The Limits of Policy Analytics: Early Examples and the Emerging Boundary of Possibilities
Politics and Governance (ISSN: 2183–2463) 2018, Volume 6, Issue 4, Pages 5–17 DOI: 10.17645/pag.v6i4.1561 Article The Limits of Policy Analytics: Early Examples and the Emerging Boundary of Possibilities Justin Longo 1,* and Rod Dobell 2 1 Johnson Shoyama Graduate School of Public Policy, University of Regina, Regina, S4S 0A2, Canada; E-Mail: [email protected] 2 Centre for Global Studies, University of Victoria, Victoria, V8P 5C2, Canada; E-Mail: [email protected] * Corresponding author Submitted: 1 May 2018 | Accepted: 19 September 2018 | Published: 21 November 2018 Abstract Policy analytics has emerged as a modification of traditional policy analysis, where the discrete stages of the policy cycle are reformulated into a continuous, real-time system of big data collection, data analytics, and ubiquitous, connected tech- nologies that provides the basis for more precise problem definition, policy experimentation for revealing detailed insights into system dynamics, and ongoing assessment of the impact of micro-scale policy interventions to nudge behaviour to- wards desired policy objectives. Theoretical and applied work in policy analytics research and practice is emerging that offers a persuasive case for the future possibilities of a real-time approach to policymaking and governance. However, policy problems often operate on long time cycles where the effect of policy interventions on behaviour and decisions can be observed only over long periods, and often only indirectly. This article surveys examples in the policy analytics literature, infers from those examples some characteristics of the policy problems and settings that lend themselves to a policy analytics approach, and suggests the boundaries of feasible policy analytics. -
Language-Based User Representations for Fake News Detection
Words are the Window to the Soul: Language-based User Representations for Fake News Detection Marco Del Tredici Raquel Fernandez´ Amazon University of Amsterdam [email protected] [email protected] Abstract Cognitive and social traits of individuals are reflected in language use. Moreover, individuals who are prone to spread fake news online often share common traits. Building on these ideas, we introduce a model that creates representations of individuals on social media based only on the language they produce, and use them to detect fake news. We show that language-based user representations are beneficial for this task. We also present an extended analysis of the language of fake news spreaders, showing that its main features are mostly domain independent and consistent across two English datasets. Finally, we exploit the relation between language use and connections in the social graph to assess the presence of the Echo Chamber effect in our data. 1 Introduction Fake news have become a problem of paramount relevance in our society, due to their large diffusion in public discourse, especially on social media, and their alarming effects on our lives (Lazer et al., 2018). Several works show that fake news played a role in major events such as the US Presidential Elections (Allcott and Gentzkow, 2017), stock market trends (Rapoza, 2017), and the Coronavirus disease outbreak (Shimizu, 2020). In NLP a considerable amount of work has been dedicated to fake news detection, i.e., the task of classifying a news as either real or fake – see Zhou and Zafarani (2020), Kumar and Shah (2018) and Oshikawa et al. -
When Machine Behavior Targets Future Voters: the Use of Social Bots to Test Narratives for Political Campaigns in Brazil
International Journal of Communication 15(2021), 1220–1243 1932–8036/20210005 When Machine Behavior Targets Future Voters: The Use of Social Bots to Test Narratives for Political Campaigns in Brazil ROSE MARIE SANTINI DÉBORA SALLES GIULIA TUCCI Federal University of Rio de Janeiro, Brazil In 2018, the election of Jair Bolsonaro for the Brazilian presidency was associated with dubious propaganda strategies implemented through social media. The purpose of this article is to understand the early development of key communication strategies of his presidential campaign since 2016. We used a combination of observational, discourse, and content analysis based on digital trace data to investigate how Bolsonaro had been testing his campaign targets and segmentation, as well as cultivating bot accounts and botnets on Twitter during the 2016 Rio de Janeiro municipal election. Our research suggests that the automation of different supporter profiles to target potential voter identities and the experimental dissemination of divisive narratives ensured the effectiveness of his communication persuasion. This finding contributes to the growing body of knowledge regarding his controversial online efforts, adding to the urgent research agenda on Brazil’s democratic setback. Keywords: social bots, campaign strategy, political narratives, disinformation, Twitter, Jair Bolsonaro, Brazil In recent years, social media platforms have been used to spread toxic content, and have been implicated in accusations of public opinion manipulation and online propaganda. Propaganda played a troubling role in boosting Jair Bolsonaro into the Brazilian presidency in 2018 (Hunter & Power, 2019). Bolsonaro, a far-right fringe figure and longtime legislative backbencher, was elected amid accusations of benefiting from a powerful and coordinated social media campaign intended to discredit his left-wing opponent (Phillips, 2018). -
The Connotation, Features, and Mechanism of Computational Propaganda
DOI 10.14746/ssp.2021.2.4 Jin YANG Moscow State University, Moscow ORCID ID: 0000-0002-5302-6664 The Connotation, Features, and Mechanism of Computational Propaganda Abstract: The purpose of the work is to identify the connotation, features of compu- tational propaganda and reveal how computational propaganda uses new technologies to manipulate public opinion. The study’s hypothesis is the assumption that computational propaganda, as a new type of propaganda and manipulation of public opinion spawned in the era of artificial intelligence, stealthily and massively steers public opinion using new technologies to influence political and social processes. With the scientific methods such as event analysis and case-study, the work con- cludes that more and more governments, political parties, and strategic communica- tion companies use social media as the digital platform, Internet bots as the automated executors, and algorithms as the computational technical guarantee, by participating in, guiding and creating controversial topics and events, to manipulate public opinion and win international competitions, policy debates, elections, etc. Key words: computational propaganda, manipulation, social media, Internet bots, algorithms Introduction nformation is power. Technology is power. When massive and compre- Ihensive information is combined with automatic and intelligent tech- nology, what changes may this bring to the world? Up to 2020, 81 countries are found to spread computational propagan- da about politics. Since 2018 there have been more than 65 firms offering computational propaganda services. Almost 60 million US dollars were spent on hiring firms for computational propaganda since 2009 (Brad- shaw, Bailey, Howard, 2021, p. 2). Computational propaganda is the intersection of technology and politics on social media, big data, and artificial intelligence. -
A Survey on Computational Politics
Received October 2, 2020, accepted October 18, 2020, date of publication October 30, 2020, date of current version November 11, 2020. Digital Object Identifier 10.1109/ACCESS.2020.3034983 A Survey on Computational Politics EHSAN UL HAQ 1, TRISTAN BRAUD 1, (Member, IEEE), YOUNG D. KWON1, AND PAN HUI 1,2, (Fellow, IEEE) 1Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR 2Department of Computer Science, University of Helsinki, 00014 Helsinki, Finland Corresponding authors: Ehsan Ul Haq ([email protected]) and Tristan Braud ([email protected]) This work was supported in part by the Research Grants Council of Hong Kong under Project 16214817, and in part by the Academy of Finland through the 5GEAR Project and FIT Project. ABSTRACT Computational Politics is the study of computational methods to analyze and moderate users' behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid development and ease of access to the Internet, Information Communication Technologies (ICT) have given rise to massive numbers of users joining online communities and the digitization of political practices such as debates. These communities and digitized data contain both explicit and latent information about users and their behaviors related to politics and social movements. For researchers, it is essential to utilize data from these sources to develop and design systems that not only provide solutions to computational politics but also help other businesses, such as marketers, to increase users' participation and interactions. In this survey, we attempt to categorize main areas in computational politics and summarize the prominent studies in one place to better understand computational politics across different and multidimensional platforms. -
A Survey on Computational Politics
A Survey on Computational Politics EHSAN UL HAQ, Hong Kong University of Science and Technology, HKSAR TRISTAN BRAUD, Hong Kong University of Science and Technology, HKSAR YOUNG D. KWON, Hong Kong University of Science and Technology, HKSAR PAN HUI, Hong Kong University of Science and Technology, HKSAR and University of Helsinki, Finland Computational Politics is the study of computational methods to analyze and moderate users’ behaviors related to political activities such as election campaign persuasion, political affiliation, and opinion mining. With the rapid development and ease of access to the Internet, Information Communication Technologies (ICT) have given rise to massive numbers of users joining online communities and the digitization of analogous data such as political debates. These communities and digitized data contain both explicit and latent information about users and their behaviors related to politics. For researchers, it is essential to utilize data from these sources to develop and design systems that not only provide solutions to computational politics but also help other businesses, such as marketers, to increase users’ participation and interactions. In this survey, we attempt to categorize main areas in computational politics and summarize the prominent studies in one place to better understand computational politics across different and multidimensional platforms. e.g., online social networks, online forums, and political debates. We then conclude this study by highlighting future research directions, opportunities, and challenges. CCS Concepts: • Human-centered computing → Social networking sites; • Social and professional topics → User characteristics; • Information systems → Content analysis and feature selection; Social recommendation; • Applied computing → Law, social and behavioral sciences. Additional Key Words and Phrases: Social Networks, Homophily, Political Affiliation, Political Discourse 1 INTRODUCTION The Internet and digitization of data, particularly in recent years, have changed the way we process information.