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Transformer-Based Quantification of the Echo Chamber Effect in Online Communities
| dc.contributor.author | Ghafouri, Vahid | |
| dc.contributor.author | Alatawi, Faisal | |
| dc.contributor.author | Karami, Mansooreh | |
| dc.contributor.author | Such, Jose | |
| dc.contributor.author | Suarez-Tangil, Guillermo | |
| dc.date.accessioned | 2024-07-15T13:23:36Z | |
| dc.date.available | 2024-07-15T13:23:36Z | |
| dc.date.issued | 2024-11-13 | |
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We demonstrate that our approach outperforms the current, state-of-the-art, density-based clustering methods on a wide variety of real world data.", isbn="978-3-642-37456-2" } @online{Grootendorst2020, author = {Maarten Grootendorst}, title = {Topic Modeling with BERT}, year = 2020, url = {https://towardsdatascience.com/topic-modeling-with-bert-779f7db187e6}, urldate = {2020-10-1} } @article{Angelov2020, title={Top2Vec: Distributed Representations of Topics}, author={Dimitar Angelov}, journal={ArXiv}, year={2020}, volume={abs/2008.09470} } @online{Borrelli2021, author = {David Borrelli}, title = {Clustering sentence embeddings to identify intents in short text}, year = 2021, url = {https://towardsdatascience.com/clustering-sentence-embeddings-to-identify-intents-in-short-text-48d22d3bf02e}, urldate = {2021-10-19} } @article{mueller-1970, title={Presidential Popularity from Truman to Johnson}, volume={64}, DOI={10.2307/1955610}, number={1}, journal={American Political Science Review}, publisher={Cambridge University Press}, author={Mueller, John E.}, year={1970}, pages={18–34}} @article{hetherington-nelson-2003, title={Anatomy of a Rally Effect: George W. Bush and the War on Terrorism}, volume={36}, DOI={10.1017/S1049096503001665}, number={1}, journal={PS: Political Science & Politics}, publisher={Cambridge University Press}, author={Hetherington, Marc J. and Nelson, Michael}, year={2003}, pages={37–42}} @article{baker, author = {William D. Baker and John R. Oneal}, title ={Patriotism or Opinion Leadership?: The Nature and Origins of the “Rally 'Round the Flag” Effect}, journal = {Journal of Conflict Resolution}, volume = {45}, number = {5}, pages = {661-687}, year = {2001}, doi = {10.1177/0022002701045005006}, URL = { https://doi.org/10.1177/0022002701045005006 }, eprint = { https://doi.org/10.1177/0022002701045005006 } , abstract = { In this study, the “rally effect”—the propensity for the American public to put aside political differences and support the president during international crises—is measured by considering the changes in presidential popularity following all 193 Militarized Interstate Disputes (MIDs) between 1933 and 1992 as identified by the Correlates of War project. Summary analyses find minor, statistically insignificant rallies associated with uses of force, although sizable rallies are associated with particular subcategories of military crises. However, larger rallies are associated with the United States as both revisionist and originator of the dispute, with the initiation of a full interstate war, and with prominent headline placement in the New York Times. Regression analyses indicate that rallies are more likely when they are associated with White House statements and bipartisan support for the administration's policies. Findings suggest that the size and appearance of a rally depends primarily on how the crisis is presented to the public in terms of media coverage, bipartisan support, and White House spin. } } @book{goldstein2008principles, title={Principles of international relations}, author={Goldstein, Joshua S and Pevehouse, Jon C and Sernau, Scott}, year={2008}, publisher={Pearson Longman} } @article{Hoff2002, author = {Peter D Hoff and Adrian E Raftery and Mark S Handcock}, title = {Latent Space Approaches to Social Network Analysis}, journal = {Journal of the American Statistical Association}, volume = {97}, number = {460}, pages = {1090-1098}, year = {2002}, publisher = {Taylor \& Francis}, doi = {10.1198/016214502388618906}, URL = { https://doi.org/10.1198/016214502388618906 }, eprint = { https://doi.org/10.1198/016214502388618906 } , abstract = { Network models are widely used to represent relational information among interacting units. In studies of social networks, recent emphasis has been placed on random graph models where the nodes usually represent individual social actors and the edges represent the presence of a specified relation between actors. We develop a class of models where the probability of a relation between actors depends on the positions of individuals in an unobserved “social space.” We make inference for the social space within maximum likelihood and Bayesian frameworks, and propose Markov chain Monte Carlo procedures for making inference on latent positions and the effects of observed covariates. We present analyses of three standard datasets from the social networks literature, and compare the method to an alternative stochastic blockmodeling approach. In addition to improving on model fit for these datasets, our method provides a visual and interpretable model-based spatial representation of social relationships and improves on existing methods by allowing the statistical uncertainty in the social space to be quantified and graphically represented. } } @article{Barbera2015, author = {Pablo Barberá and John T. Jost and Jonathan Nagler and Joshua A. Tucker and Richard Bonneau}, title ={Tweeting From Left to Right: Is Online Political Communication More Than an Echo Chamber?}, journal = {Psychological Science}, volume = {26}, number = {10}, pages = {1531-1542}, year = {2015}, doi = {10.1177/0956797615594620}, note ={PMID: 26297377}, URL = { https://doi.org/10.1177/0956797615594620 }, eprint = { https://doi.org/10.1177/0956797615594620 } , abstract = { We estimated ideological preferences of 3.8 million Twitter users and, using a dataset of nearly 150 million tweets concerning 12 political and nonpolitical issues, explored whether online communication resembles an “echo chamber” (as a result of selective exposure and ideological segregation) or a “national conversation.” We observed that information was exchanged primarily among individuals with similar ideological preferences in the case of political issues (e.g., 2012 presidential election, 2013 government shutdown) but not many other current events (e.g., 2013 Boston Marathon bombing, 2014 Super Bowl). Discussion of the Newtown shootings in 2012 reflected a dynamic process, beginning as a national conversation before transforming into a polarized exchange. With respect to both political and nonpolitical issues, liberals were more likely than conservatives to engage in cross-ideological dissemination; this is an important asymmetry with respect to the structure of communication that is consistent with psychological theory and research bearing on ideological differences in epistemic, existential, and relational motivation. Overall, we conclude that previous work may have overestimated the degree of ideological segregation in social-media usage. } } @article{Kursuncu2019, author = {Kursuncu, Ugur and Gaur, Manas and Castillo, Carlos and Alambo, Amanuel and Thirunarayan, Krishnaprasad and Shalin, Valerie and Achilov, Dilshod and Arpinar, I. Budak and Sheth, Amit}, title = {Modeling Islamist Extremist Communications on Social Media Using Contextual Dimensions: Religion, Ideology, and Hate}, year = {2019}, issue_date = {November 2019}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {3}, number = {CSCW}, url = {https://doi.org/10.1145/3359253}, doi = {10.1145/3359253}, abstract = {Terror attacks have been linked in part to online extremist content. Online conversations are cloaked in religious ambiguity, with deceptive intentions, often twisted from mainstream meaning to serve a malevolent ideology. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremist and mainstream contexts challenge machine interpretation, with a particular threat to the precision of classification algorithms. Radicalization is a subtle long-running persuasive process that occurs over time. Our context-aware computational approach to the analysis of extremist content on Twitter breaks down this persuasion process into building blocks that acknowledge inherent ambiguity and sparsity that likely challenge both manual and automated classification. Based on prior empirical and qualitative research in social sciences, particularly political science, we model this process using a combination of three contextual dimensions -- religion, ideology, and hate -- each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible. We utilize domain-specific knowledge resources for each of these contextual dimensions such as Qur'an for religion, the books of extremist ideologues and preachers for political ideology and a social media hate speech corpus for hate. The significant sensitivity of the Islamist extremist ideology and its local and global security implications require reliable algorithms for modelling such communications on Twitter. Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate, which reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming. Given the potentially significant social impact, we evaluate the performance of our algorithms to minimize mislabeling, where our context-aware approach outperforms a competitive baseline by 10.2\% in precision, thereby enhancing the potential of such tools for use in human review.}, journal = {Proc. ACM Hum.-Comput. Interact.}, month = {nov}, articleno = {151}, numpages = {22}, keywords = {multi-dimensional modeling, islamist extremism, contextual dimensions, user modeling, radicalization} } @inproceedings{Arora2017, title={A Simple but Tough-to-Beat Baseline for Sentence Embeddings}, author={Sanjeev Arora and Yingyu Liang and Tengyu Ma}, booktitle={ICLR}, year={2017} } @inproceedings{gu2021exploiting, title={Exploiting behavioral consistence for universal user representation}, author={Gu, Jie and Wang, Feng and Sun, Qinghui and Ye, Zhiquan and Xu, Xiaoxiao and Chen, Jingmin and Zhang, Jun}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence}, volume={35}, number={5}, pages={4063--4071}, year={2021} } @inproceedings{amir2016modelling, title={Modelling Context with User Embeddings for Sarcasm Detection in Social Media}, author={Amir, Silvio and Wallace, Byron C and Lyu, Hao and Carvalho, Paula and Silva, Mario J}, booktitle={Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning}, pages={167--177}, year={2016} } @inproceedings{preoctiuc2017beyond, title={Beyond binary labels: political ideology prediction of twitter users}, author={Preo{\c{t}}iuc-Pietro, Daniel and Liu, Ye and Hopkins, Daniel and Ungar, Lyle}, booktitle={Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, pages={729--740}, year={2017} } @inproceedings{ding2017multi, title={Multi-view unsupervised user feature embedding for social media-based substance use prediction}, author={Ding, Tao and Bickel, Warren K and Pan, Shimei}, booktitle={Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing}, pages={2275--2284}, year={2017} } @article{pan2019social, title={Social media-based user embedding: A literature review}, author={Pan, Shimei and Ding, Tao}, journal={Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19)}, year={2019} } @inproceedings{garimella2017, title={A long-term analysis of polarization on Twitter}, author={Garimella, Venkata Rama Kiran and Weber, Ingmar}, booktitle={Eleventh international AAAI conference on web and social media}, year={2017} } @article{Esteban1994, ISSN = {00129682, 14680262}, URL = {http://www.jstor.org/stable/2951734}, abstract = {Suppose that a population of individuals may be grouped according to some vector of characteristics into "clusters," such that each cluster is very "similar" in terms of the attributes of its members, but different clusters have members with very "dissimilar" attributes. 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So far, much research has examined large-scale dissemination patterns of prominent statements, opinions, and slogans circulated on social media, such as the analysis of keywords and hashtags on Twitter regarding a political event. However, little attention has been paid to understanding how local socio-cultural-political conditions influence the formation and development of public discourses on social media. To explore this question, we analyzed public discourses about Hong Kong's Umbrella Movement on two distinct social media sites, Facebook and Weibo, the largest micro-blogging service in China. Facebook topped Hong Kong citizens' usage of social media sites, while Weibo's primary user base is mainland Chinese. The social movement and these two social media sites provide a unique opportunity to explore the commonalities and differences between social media discourses generated by two different cultures. Using grounded theory and discourse analysis, we reveal how people on two sites reasoned about the many incidents of the movement and developed sometimes similar but other times strikingly different discourses. We trace the links between different discourses and the socio-cultural-political conditions of Hong Kong and mainland China. We discuss how this study may contribute deeper understandings of public discourses on social media to the CSCW literature.}, journal = {Comput. Supported Coop. Work}, month = {dec}, pages = {807–836}, numpages = {30}, keywords = {Synchronicity, Localness of social media discourse, Facebook, Weibo, Social media, Hong Kong, Discourse analysis, Umbrella movement, Public discourse, China} } @inproceedings{Liao2014cscw, author = {Liao, Q. Vera and Fu, Wai-Tat}, title = {Can You Hear Me Now? Mitigating the Echo Chamber Effect by Source Position Indicators}, year = {2014}, isbn = {9781450325400}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/2531602.2531711}, doi = {10.1145/2531602.2531711}, abstract = {We examined how a source position indicator showing both valences (pro/con) and magnitudes (moderate/extreme) of positions on controversial topics influenced users' selection and reception of diverse opinions in online discussions. Results showed that the indicator had differential impact on participants who had varied levels of accuracy motives -- i.e., motivation to accurately learn about the topic, by leading to greater exposure to attitude-challenging information for participants with higher accuracy motives. Further analysis revealed that it was mainly caused by the fact that the presence of position indicator increased the selection of moderately inconsistent sources for participants with high accuracy motives but decreased the selection of them for participants with low accuracy motives. The indicator also helped participants differentiate between sources with moderate and extreme positions, and increased their tendency to agree with attitude-challenging information from sources with moderately inconsistent positions. Participants with high accuracy motives were also found to learn significantly more about the arguments put forward by the opposite side with the help of the position indicator. We discussed the implications of the results for the nature of the echo chamber effect, as well as for designing information systems that encourage seeking of diverse information and common ground seeking.}, booktitle = {Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work \& Social Computing}, pages = {184–196}, numpages = {13}, keywords = {selective exposure, motivation, information diversity}, location = {Baltimore, Maryland, USA}, series = {CSCW '14} } @inproceedings{Semaan2014cscw, author = {Semaan, Bryan C. and Robertson, Scott P. and Douglas, Sara and Maruyama, Misa}, title = {Social Media Supporting Political Deliberation across Multiple Public Spheres: Towards Depolarization}, year = {2014}, isbn = {9781450325400}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/2531602.2531605}, doi = {10.1145/2531602.2531605}, abstract = {This paper reports on a qualitative study of social media use for political deliberation by 21 U.S. citizens. In observing people's interactions in the "sprawling public sphere" across multiple social media tools in both political and non-political spaces, we found that social media supported the interactional dimensions of deliberative democracy--the interaction with media and the interaction between people. People used multiple tools through which they: were serendipitously exposed to diverse political information, constructed diverse information feeds, disseminated diverse information, and engaged in respectful and reasoned political discussions with diverse audiences. When people's civic agency was inhibited when using a tool, they often adopted, or switched to, alternative media that could afford what they were trying to achieve. Contrary to the polarization perspective, we find that people were purposefully seeking diverse information and discussants. Some individuals altered their views as a result of the interactions they were having in the online public sphere.}, booktitle = {Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work \& Social Computing}, pages = {1409–1421}, numpages = {13}, keywords = {public sphere, multi-mediation, depolarization, social media}, location = {Baltimore, Maryland, USA}, series = {CSCW '14} } @inproceedings{Borge2015cscw, author = {Borge-Holthoefer, Javier and Magdy, Walid and Darwish, Kareem and Weber, Ingmar}, title = {Content and Network Dynamics Behind Egyptian Political Polarization on Twitter}, year = {2015}, isbn = {9781450329224}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/2675133.2675163}, doi = {10.1145/2675133.2675163}, abstract = {There is little doubt about whether social networks play a role in modern protests. This agreement has triggered an entire research avenue, in which social structure and content analysis have been central - but are typically exploited separately. Here, we combine these two approaches to shed light on the opinion evolution dynamics in Egypt during the summer of 2013 along two axes (Islamist/Secularist, pro/anti-military intervention). We intend to find traces of opinion changes in Egypt's population, paralleling those in the international community - which oscillated from sympathetic to condemnatory as civil clashes grew. We find little evidence of people "switching" sides but observe clear changes in volume with both pro- and anti-military camps becoming more active at different stages. Our work contributes new insights into the dynamics of large protest movements, specially in the aftermath of the main events - rather unattended previously. It questions the standard narrative concerning a simplistic mapping between Secularist/pro-military and Islamist/anti-military. Finally, our conclusions provide empirical validation to sociological models regarding the behavior of individuals in conflictive contexts.}, booktitle = {Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work \& Social Computing}, pages = {700–711}, numpages = {12}, keywords = {egypt, polarization, mobilization, twitter, opinion switch}, location = {Vancouver, BC, Canada}, series = {CSCW '15} } @inproceedings{Bruns2019interchangably, title={It’s not the technology, stupid: How the ‘Echo Chamber’ and ‘Filter Bubble’ metaphors have failed us}, author={Axel Bruns}, year={2019} } @techreport{Ross2022interchangably, edition = {}, number = {}, journal = {}, pages = {}, publisher = {Reuters Institute for the Study of Journalism}, school = {}, title = {Echo chambers, filter bubbles, and polarisation: a literature review }, volume = {}, author = {Ross Arguedas, A and Robertson, C and Fletcher, R and Nielsen, R}, editor = {}, year = {2022}, series = {} } @incollection{Bruns2021interchangably, title={Echo chambers? Filter bubbles? The misleading metaphors that obscure the real problem}, author={Bruns, Axel}, booktitle={Hate speech and polarization in participatory society}, pages={33--48}, year={2021}, publisher={Routledge} } @article{garimella2018polarization, title={Polarization on social media}, author={Garimella, Kiran and others}, year={2018}, publisher={Aalto University} } @misc{gallup2013demvsrep, author = "Newport, Frank", title = "Democrats Racially Diverse; Republicans Mostly White", howpublished = "Online post", month = "February", year = "2013", note = "Accessed on July 5th, 2023", url = "https://news.gallup.com/poll/160373/democrats-racially-diverse-republicans-mostly-white.aspx", } @Article{sun2022homogeneity, AUTHOR = {Sun, Mingfei and Ma, Xiaoyue and Huo, Yudi}, TITLE = {Does Social Media Users' Interaction Influence the Formation of Echo Chambers? Social Network Analysis Based on Vaccine Video Comments on YouTube}, JOURNAL = {International Journal of Environmental Research and Public Health}, VOLUME = {19}, YEAR = {2022}, NUMBER = {23}, ARTICLE-NUMBER = {15869}, URL = {https://www.mdpi.com/1660-4601/19/23/15869}, PubMedID = {36497977}, ISSN = {1660-4601}, ABSTRACT = {The characteristics and influence of the echo chamber effect (TECE) of health misinformation diffusion on social media have been investigated by researchers, but the formation mechanism of TECE needs to be explored specifically and deeply. This research focuses on the influence of users' limitation, intergroup interaction, and reciprocity behavior on TECE based on the social contagion mechanism. A user comment' reply social network was constructed using the comments of a COVID-19 vaccine video on YouTube. The semantic similarity and Exponential Random Graph Model (ERGM) were used to calculate TECE and the effect of three interaction mechanisms on the echo chamber. The results show that there is a weak echo chamber effect (ECE) in the spread of misinformation about the COVID-19 vaccine. The imitation and intergroup interaction behavior are positively related to TECE. Reciprocity has no significant influence on TECE.}, DOI = {10.3390/ijerph192315869} } @article{Grusauskaite2023, author = {Kamile Grusauskaite and Luca Carbone and Jaron Harambam and Stef Aupers}, title ={Debating (in) echo chambers: How culture shapes communication in conspiracy theory networks on YouTube}, journal = {New Media \& Society}, volume = {0}, number = {0}, pages = {14614448231162585}, year = {2023}, doi = {10.1177/14614448231162585}, URL = { https://doi.org/10.1177/14614448231162585 }, eprint = { https://doi.org/10.1177/14614448231162585 } , abstract = { The ubiquity of social media platforms fuels heated discussions about algorithms and selection biases leading people into online “echo chambers.” Scholars argue that social media deepen societal polarization and fuel political extremism. However, studies often focus on media effects, disregarding individual agency and (sub)cultural values that shape communication. As a strategic case study, this article, based on a mixed-methods analysis, including a social network and qualitative analysis of 1199 comments under four conspiracy theory comment sections on YouTube, questions how insular these spaces are? And how people in these networks communicate? We find that the discussions in our strategically sampled comments sections lie between homogeneous closed debates and open debates. In other words, the networks in our sample vary in their “echo chamberness.” Based on our findings, we contend that variations in the echo chamberness of the various comment sections can be explained via the lens of conspiratorial (sub)cultures. } } @article{gao2023echo, author = {Gao, Y. and Liu, F. and Gao, L.}, title = {Echo chamber effects on short video platforms}, journal = {Sci Rep}, volume = {13}, pages = {6282}, year = {2023}, doi = {10.1038/s41598-023-33370-1}, } @article{koch, author = {Natalie Koch}, title = {The problem with rallying around the (Ukrainian) flag}, journal = {Space and Polity}, volume = {0}, number = {0}, pages = {1-5}, year = {2023}, publisher = {Routledge}, doi = {10.1080/13562576.2023.2223129} } @inproceedings{ghafouriGPT, author = {Ghafouri, Vahid and Agarwal, Vibhor and Zhang, Yong and Sastry, Nishanth and Such, Jose and Suarez-Tangil, Guillermo}, title = {AI in the Gray: Exploring Moderation Policies in Dialogic Large Language Models vs. Human Answers in Controversial Topics}, year = {2023}, isbn = {9798400701245}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3583780.3614777}, doi = {10.1145/3583780.3614777}, abstract = {The introduction of ChatGPT and the subsequent improvement of Large Language Models (LLMs) have prompted more and more individuals to turn to the use of ChatBots, both for information and assistance with decision-making. However, the information the user is after is often not formulated by these ChatBots objectively enough to be provided with a definite, globally accepted answer.Controversial topics, such as "religion", "gender identity", "freedom of speech", and "equality", among others, can be a source of conflict as partisan or biased answers can reinforce preconceived notions or promote disinformation. By exposing ChatGPT to such debatable questions, we aim to understand its level of awareness and if existing models are subject to socio-political and/or economic biases. We also aim to explore how AI-generated answers compare to human ones. For exploring this, we use a dataset of a social media platform created for the purpose of debating human-generated claims on polemic subjects among users, dubbed Kialo.Our results show that while previous versions of ChatGPT have had important issues with controversial topics, more recent versions of ChatGPT (gpt-3.5-turbo) are no longer manifesting significant explicit biases in several knowledge areas. In particular, it is well-moderated regarding economic aspects. However, it still maintains degrees of implicit libertarian leaning toward right-winged ideals which suggest the need for increased moderation from the socio-political point of view. In terms of domain knowledge on controversial topics, with the exception of the "Philosophical" category, ChatGPT is performing well in keeping up with the collective human level of knowledge. Finally, we see that sources of Bing AI have slightly more tendency to the center when compared to human answers. All the analyses we make are generalizable to other types of biases and domains.}, booktitle = {Proceedings of the 32nd ACM International Conference on Information and Knowledge Management}, pages = {556–565}, numpages = {10}, keywords = {ChatGPT, AI bias, sentence transformers, controversial topics, NLP, Kialo}, location = {Birmingham, United Kingdom}, series = {CIKM '23} } @inproceedings{Salamat-disentaglement, author = {Salamat, Sara and Arabzadeh, Negar and Seyedsalehi, Shirin and Bigdeli, Amin and Zihayat, Morteza and Bagheri, Ebrahim}, title = {Neural Disentanglement of Query Difficulty and Semantics}, year = {2023}, isbn = {9798400701245}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3583780.3615189}, doi = {10.1145/3583780.3615189}, abstract = {Researchers have shown that the retrieval effectiveness of queries may depend on other factors in addition to the semantics of the query. In other words, several queries expressed with the same intent, and even using overlapping keywords, may exhibit completely different degrees of retrieval effectiveness. As such, the objective of our work in this paper is to propose a neural disentanglement method that is able to disentangle query semantics from query difficulty. The disentangled query semantics representation provides the means to determine semantic association between queries whereas the disentangled query difficulty representation would allow for the estimation of query effectiveness. We show through our experiments on the query performance prediction; and, query similarity calculation tasks that our proposed disentanglement method is able to show better performance compared to the state of the art.}, booktitle = {Proceedings of the 32nd ACM International Conference on Information and Knowledge Management}, pages = {4264–4268}, numpages = {5}, keywords = {disentanglement, query performance prediction, information retrieval}, location = {Birmingham, United Kingdom}, series = {CIKM '23} } @article{Coletto-SXSW, title={Automatic controversy detection in social media: A content-independent motif-based approach}, author={Mauro Coletto and Venkata Rama Kiran Garimella and A. Gionis and Claudio Lucchese}, journal={Online Soc. Networks Media}, year={2017}, volume={3-4}, pages={22-31}, url={https://api.semanticscholar.org/CorpusID:54300115} } @mastersthesis{ghafouri-thesis, author = {Ghafouri, Vahid and RezaeeDaryakenari, Babak and Kasap, Nihat}, title = {Who rallies around the flag? Analyzing the impact of foreign interventions on nations' political stance using social media data}, year = {2020}, school = {Sabancı University}, type = {Master's Thesis}, note = {[Thesis]}, url = {https://risc01.sabanciuniv.edu/record=b2473816}, } @inproceedings{He2023migration, author = {He, Jiahui and Zia, Haris Bin and Castro, Ignacio and Raman, Aravindh and Sastry, Nishanth and Tyson, Gareth}, title = {Flocking to Mastodon: Tracking the Great Twitter Migration}, year = {2023}, isbn = {9798400703829}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3618257.3624819}, doi = {10.1145/3618257.3624819}, abstract = {The acquisition of Twitter by Elon Musk has spurred controversy and uncertainty among Twitter users. The move raised both praise and concerns, particularly regarding Musk's views on free speech. As a result, a large number of Twitter users have looked for alternatives to Twitter. Mastodon, a decentralized micro-blogging social network, has attracted the attention of many users and the general media. In this paper, we analyze the migration of 136,009 users from Twitter to Mastodon. We inspect the impact that this has on the wider Mastodon ecosystem, particularly in terms of user-driven pressure towards centralization. We further explore factors that influence users to migrate, highlighting the effect of users' social networks. Finally, we inspect the behavior of individual users, showing how they utilize both Twitter and Mastodon in parallel. We find a clear difference in the topics discussed on the two platforms. This leads us to build classifiers to explore if migration is predictable. Through feature analysis, we find that the content of tweets as well as the number of URLs, the number of likes, and the length of tweets are effective metrics for the prediction of user migration.}, booktitle = {Proceedings of the 2023 ACM on Internet Measurement Conference}, pages = {111–123}, numpages = {13}, keywords = {user migration, twitter, topic modeling, mastodon, machine learning}, location = {Montreal QC, Canada}, series = {IMC '23} } @article{Slater2018nonwestpol, title={Polarizing Figures: Executive Power and Institutional Conflict in Asian Democracies}, author={D. Slater and A. Arugay}, journal={American Behavioral Scientist}, year={2018}, volume={62}, pages={106 - 92}, doi={10.1177/0002764218759577} } @article{Abramowitz2010nonwestpol, title={The Disappearing Center: Engaged Citizens, Polarization, and American Democracy}, author={A. Abramowitz}, year={2010}, doi={10.5860/choice.48-1737} } @article{Ribberink2018ReligiousPol, title={Religious polarization: contesting religion in secularized Western European countries}, author={Egbert Ribberink and P. Achterberg and D. Houtman}, journal={Journal of Contemporary Religion}, year={2018}, volume={33}, pages={209 - 227}, doi={10.1080/13537903.2018.1469262} } @article{jacomy2014forcedatlas2, doi = {10.1371/journal.pone.0098679}, author = {Jacomy, Mathieu AND Venturini, Tommaso AND Heymann, Sebastien AND Bastian, Mathieu}, journal = {PLOS ONE}, publisher = {Public Library of Science}, title = {ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software}, year = {2014}, month = {06}, volume = {9}, url = {https://doi.org/10.1371/journal.pone.0098679}, pages = {1-12}, abstract = {Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users’ typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.}, number = {6}, } @article{Bailon2023FacebookPolarization, author = {Sandra González-Bailón and David Lazer and Pablo Barberá and Meiqing Zhang and Hunt Allcott and Taylor Brown and Adriana Crespo-Tenorio and Deen Freelon and Matthew Gentzkow and Andrew M. Guess and Shanto Iyengar and Young Mie Kim and Neil Malhotra and Devra Moehler and Brendan Nyhan and Jennifer Pan and Carlos Velasco Rivera and Jaime Settle and Emily Thorson and Rebekah Tromble and Arjun Wilkins and Magdalena Wojcieszak and Chad Kiewiet de Jonge and Annie Franco and Winter Mason and Natalie Jomini Stroud and Joshua A. Tucker }, title = {Asymmetric ideological segregation in exposure to political news on Facebook}, journal = {Science}, volume = {381}, number = {6656}, pages = {392-398}, year = {2023}, doi = {10.1126/science.ade7138}, URL = {https://www.science.org/doi/abs/10.1126/science.ade7138}, eprint = {https://www.science.org/doi/pdf/10.1126/science.ade7138}, abstract = {Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election using aggregated data for 208 million US Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged. We show that (i) ideological segregation is high and increases as we shift from potential exposure to actual exposure to engagement; (ii) there is an asymmetry between conservative and liberal audiences, with a substantial corner of the news ecosystem consumed exclusively by conservatives; and (iii) most misinformation, as identified by Meta’s Third-Party Fact-Checking Program, exists within this homogeneously conservative corner, which has no equivalent on the liberal side. Sources favored by conservative audiences were more prevalent on Facebook’s news ecosystem than those favored by liberals.} } @article{Tornberg2018misinformation, title={Echo chambers and viral misinformation: Modeling fake news as complex contagion}, author={P. Törnberg}, journal={PLoS ONE}, year={2018}, volume={13}, doi={10.1371/journal.pone.0203958} } @article{Treviranus2009criticalthinking, title={The value of the unpopular: Counteracting the popularity echo-chamber on the Web},author={J. Treviranus and S. Hockema},journal={2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH)},year={2009},pages={603-608},doi={10.1109/TIC-STH.2009.5444430} } @article{Brugnoli2019Recursive, title={Recursive patterns in online echo chambers},author={Emanuele Brugnoli and Matteo Cinelli and W. Quattrociocchi and Antonio Scala},journal={Scientific Reports},year={2019},volume={9},doi={10.1038/s41598-019-56191-7}} @article{Wang2021Covid, title={Echo Chamber Effect in Rumor Rebuttal Discussions About COVID-19 in China: Social Media Content and Network Analysis Study}, author={Dandan Wang and Yuxing Qian}, journal={Journal of Medical Internet Research}, year={2021}, volume={23}, doi={10.2196/27009} } @article{langer2022gender, title={Gender is a complex number and the case for trans phantoms}, author={Langer, SJ}, journal={Studies in Gender and Sexuality}, volume={23}, number={2}, pages={136--145}, year={2022}, publisher={Taylor \& Francis} } @article{pieterse1997deconstructing, title={Deconstructing/reconstructing ethnicity}, author={Pieterse, Jan Nederveen}, journal={Nations and Nationalism}, volume={3}, number={3}, pages={365--395}, year={1997}, publisher={Wiley Online Library} } @article{Wang2023taiwan, author = {Austin Horng-En Wang and Yao-Yuan Yeh and Charles K.S. Wu and Fang-Yu Chen}, title ={Why Does Taiwan Identity Decline?}, journal = {Journal of Asian and African Studies}, pages = {00219096231168068}, year = {2023}, doi = {10.1177/00219096231168068}, abstract = { Since 1992, the percentage of Taiwanese identifying as “Taiwanese only” increased by 50\%. The literature explains the increase by generation, democratization, and military threat. None of these foresees the decline of Taiwan identity between 2016 and 2018. We argue that the decline can be explained by issue ownership+hedging. After the Democratic Progress Party (DPP) won both the presidency and the Congress for the first time in 2016, DPP’s performance was used by voters to evaluate the utility of Taiwan identity. Propensity score matching and regressions on three groups of surveys (TEDS, TISS, and TNSS) support the theory and rule out alternative explanations. } } @article{asik2024secularism, author = {Ozan Aşık}, title ={Ideology, Polarization, and News Culture: The Secular-Islamist Tension in Turkish Journalism}, journal = {The International Journal of Press/Politics}, volume = {29}, number = {2}, pages = {530-547}, year = {2024}, doi = {10.1177/19401612221132716}, URL = { https://doi.org/10.1177/19401612221132716 }, eprint = { https://doi.org/10.1177/19401612221132716 } , abstract = { What role does political ideology play in the production of news in a contentious cultural context? To address this question, this article investigates how Turkish Islamic conservative journalists produced and circulated representations of two dramatic uprisings in 2013: the Gezi Park protests in Turkey and the military coup in Egypt. I chose these two cases because the Islamic political bias and activism that shaped the production of news about these two events are symptomatic of the way in which Islamism as a political ideology instrumentalizes news making. Based on newsroom ethnography conducted at an Islamic national mainstream television channel in Turkey between 2011 and 2014, the article demonstrates how Islamism shapes the ways in which Islamic conservative journalists interpreted and articulated the two events in the newsroom, and represented them in news coverage. In this context, journalistic practice gains an ideological character when the journalists utilize journalistic representations as strategic instruments to advance the political agenda of Islamic conservatives against secular forces in Turkey. As the polarization between Islamic and secular groups is based on cultural distinctions, I argue that the political ideology determining journalistic practices is defined not only by party affiliations or socioeconomic class positions but also by the common cultural ways of living and thinking of journalists who work and live as members of a sociocultural group. Islamic ideology serves as a social cement that creates bonds among the IslamicTV journalists as a sociocultural group, and a degree of unity and common purpose in their professional practices. } } @article{Tabaar2020iranvsturkey, author = {Ayatollahi Tabaar, Mohammad and Yildirim, A.Kadir}, title = "{Religious Parties and Ideological Change: A Comparison of Iran and Turkey}", journal = {Political Science Quarterly}, volume = {135}, number = {4}, pages = {697-723}, year = {2020}, month = {08}, abstract = "{RELIGIOUS PARTIES AND THEIR IDEOLOGIES have captured the imagination of academic scholarship and public discussion since the 1980s. Specifically, Islamist parties have become a focal point as they entered the electoral politics of many Middle Eastern countries. Much of this focus is devoted to how such parties engage in ideological moderation—a legitimate academic concern with important practical implications for democratic governance, pluralism, and violence. Observers often treat religious ideology either as a fixed attribute on one extreme, or as an entirely malleable and instrumental feature on the other. For example, the Turkish president and leader of the Justice and Development Party (AKP), Recep Tayyip Erdoğan, has been criticized since his rise to political prominence in the mid-1990s for being too ideologically rigid and threatening secularism in Turkey, gradually moving the country closer to a theocracy.1 Simultaneously, Erdoğan is characterized as a political opportunist who has no ideological commitments and exploits religion with reckless abandon to serve his own political interests.2 Yet these two seemingly conflicting views are not incompatible.}", issn = {0032-3195}, doi = {10.1002/polq.13097}, url = {https://doi.org/10.1002/polq.13097}, eprint = {https://academic.oup.com/psq/article-pdf/135/4/697/48808715/psquar\_135\_4\_697.pdf}, } @article{Azmanova2011leftright, author = {Azmanova, Albena}, title = "{After the Left–Right (Dis)continuum: Globalization and the Remaking of Europe's Ideological Geography}", journal = {International Political Sociology}, volume = {5}, number = {4}, pages = {384-407}, year = {2011}, month = {12}, abstract = "{This article examines the status of globalization as a causal factor in political mobilization and proposes a research agenda for diagnosing the impact of global socio-economic dynamics on ideological orientation in national polities. Focusing on Europe's established democracies, the article outlines recent shifts in Europe's ideological landscape and explores the mechanisms generating a new pattern of political conflict and electoral competition. It advances the hypothesis that the knowledge economy of open borders has brought about a political cleavage intimately linked to citizens’ perceptions of the social impact of global economic integration. In this context, the polarization of life chances is determined by institutionally mediated exposure to both the economic opportunities and the hazards of globalization. Fostered by the increasing relevance of the international for state-bound publics, new fault-lines of social conflict are emerging, giving shape to a new, “opportunity-risk,” axis of political competition. As the novel political cleavage challenges the conventional left–right divide, it is likely to radically alter Europe's ideological geography.}", issn = {1749-5679}, doi = {10.1111/j.1749-5687.2011.00141.x}, } | es |
| dc.identifier.uri | https://hdl.handle.net/20.500.12761/1829 | |
| dc.description.abstract | An Echo Chamber on social media refers to the environment where like-minded people hear the echo of each others' voices, opinions, or beliefs, which reinforce their own. Echo Chambers can turn social media platforms into collaborative venues that polarize and radicalize users rather than broadening their exposure to diverse information. Having a quantified metric for measuring the Echo Chamber effect can aid moderators and policymakers in tracking and mitigating online polarization and radicalization. Existing methods for Echo Chamber detection are either one-dimensional, only considering the network behavior of users while ignoring their semantic behavior, or require demanding supervised labeling, which is both expensive and less generalizable. This paper proposes a new metric to quantify the Echo Chamber effect using Transformer models for context-sensitive processing of natural language (NLP). Our metric quantifies (1) the effect of an Echo Chamber through the inverse effect of user diversity, and (2) polarization by means of user separability between two Echo Chambers in a topic. Leveraging this metric, we further propose an NLP-based embedding that represents the users' activity. Our model is simultaneously effective, computationally cheap, and unsupervised. As our method is unsupervised, it makes existing collaborative moderation efforts to thwart Echo Chamber effects more efficient by addressing the problem of identifying narrow information bases for algorithmic biases and misinformation detection. We run our analysis on three recent highly controversial political topics and a non-controversial topic: Russo-Ukrainian War, Abortion, Gun-Control, and SXSW music festival. Our results offer data-driven findings such as a higher Echo Chamber effect among Republicans over Democrats and diverse explicit support for Ukraine, especially among Democrats. We also observe a direct relationship between the Echo Chamber effect and polarization while observing that the low Echo Chamber effect for the Russo-Ukraine war is accompanied by a low polarization; and vice versa for Gun-Control. | es |
| dc.description.sponsorship | ESF Investing in your future | es |
| dc.description.sponsorship | Spanish Ministry of Science and Innovation | es |
| dc.description.sponsorship | UK's Research Centre on Privacy, Harm Reduction & Adversarial Influence online | es |
| dc.description.sponsorship | European Union-NextGenerationEU | es |
| dc.language.iso | eng | es |
| dc.title | Transformer-Based Quantification of the Echo Chamber Effect in Online Communities | es |
| dc.type | conference object | es |
| dc.conference.date | 9-13 November 2024 | es |
| dc.conference.place | San Jose, Costa Rica | es |
| dc.conference.title | ACM Conference on Computer-Supported Cooperative Work and Social Computing | * |
| dc.event.type | conference | es |
| dc.pres.type | paper | es |
| dc.type.hasVersion | AM | es |
| dc.rights.accessRights | open access | es |
| dc.relation.projectID | MCIN/AEI/10.13039/501100011033 | es |
| dc.relation.projectID | EP/V011189/1 | es |
| dc.relation.projectID | RYC-2020-029401-I | es |
| dc.relation.projectID | TED2021-132900A-I00 | es |
| dc.relation.projectName | COMET | es |
| dc.relation.projectName | REPHRAIN | es |
| dc.relation.projectName | PROM | es |
| dc.relation.projectName | 2019 Ramon y Cajal fellow | es |
| dc.description.refereed | TRUE | es |
| dc.description.status | inpress | es |
