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Quantification of Echo Chambers : A Methodological Framework Considering Multi-party Systems

Title data

Markgraf, Moritz ; Schoch, Manfred:
Quantification of Echo Chambers : A Methodological Framework Considering Multi-party Systems.
2019
Event: 27th European Conference on Information Systems (ECIS) , 08.-14.06.2019 , Stockholm and Uppsala, Sweden.
(Conference item: Conference , Speech )

Official URL: Volltext

Abstract in another language

The possibility of distributing user-generated content through online social networks (OSNs) has had liberating effects on society, with prominent examples such as the Arab Spring. Yet, since then, many dark sides of OSNs have been brought up. An example is the echo chambers phenomenon. Theory sug-gests that cognitive dissonance causes individuals to associate themselves with groups of like-minded individuals that are only exposed to content that confirms their previously held beliefs. In turn, deliber-ation amongst segregated groups increases social extremism and causes polarization, rather than mod-eration. Previous research endeavors to identify echo chambers in OSNs have scarcely investigated the community structures of a network on a fine granular level, specifically in the context of multi-party systems. To contribute to the scientific body of knowledge, we propose a framework that summarizes existing work and outlines a way for future research to fill this void. We further propose a new way to measure homophily in multi-party systems based on the cosine similarity between users. We evaluate our framework through real world data and find that members of the political right experience the least amount of crosscutting communication and the highest degrees of homophily.

Further data

Item Type: Conference item (Speech)
Refereed: Yes
Keywords: Echo Chambers; Community Detection; Multi-party System; Homophily; Twitter
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Fraunhofer Project Group Business and Information Systems Engineering
Research Institutions > Affiliated Institutes > FIM Research Center Finance & Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 27 May 2019 13:19
Last Modified: 22 Aug 2019 05:20
URI: https://eref.uni-bayreuth.de/id/eprint/49111