Name
Title | ||
|---|---|---|
Public discourse and news consumption on online social media: A quantitative, cross-platform analysis of the Italian Referendum. |
Abstract | ||
|---|---|---|
The rising attention to the spreading of fake news and unsubstantiated rumors on online social media and the pivotal role played by confirmation bias led researchers to investigate different aspects of the phenomenon. Experimental evidence showed that confirmatory information gets accepted even if containing deliberately false claims while dissenting information is mainly ignored or might even increase group polarization. It seems reasonable that, to address misinformation problem properly, we have to understand the main determinants behind content consumption and the emergence of narratives on online social media. In this paper we address such a challenge by focusing on the discussion around the Italian Constitutional Referendum by conducting a quantitative, cross-platform analysis on both Facebook public pages and Twitter accounts. We observe the spontaneous emergence of well-separated communities on both platforms. Such a segregation is completely spontaneous, since no categorization of contents was performed a priori. By exploring the dynamics behind the discussion, we find that users tend to restrict their attention to a specific set of Facebook pages/Twitter accounts. Finally, taking advantage of automatic topic extraction and sentiment analysis techniques, we are able to identify the most controversial topics inside and across both platforms. We measure the distance between how a certain topic is presented in the posts/tweets and the related emotional response of users. Our results provide interesting insights for the understanding of the evolution of the core narratives behind different echo chambers and for the early detection of massive viral phenomena around false claims. |
Year | Venue | Field |
|---|---|---|
2017 | arXiv: Social and Information Networks | Confirmation bias,Internet privacy,False accusation,Sociology,Artificial intelligence,Categorization,World Wide Web,Social media,Sentiment analysis,Misinformation,Referendum,Machine learning,restrict |
DocType | Volume | Citations |
Journal | abs/1702.06016 | 2 |
PageRank | References | Authors |
0.38 | 3 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michela Del Vicario | 1 | 131 | 12.26 |
| Sabrina Gaito | 2 | 209 | 29.64 |
| Walter Quattrociocchi | 3 | 19 | 4.88 |
| Matteo Zignani | 4 | 85 | 13.07 |
| Fabiana Zollo | 5 | 92 | 10.11 |