Schmidt, Ana Lucia (2018) A quantitative analysis of news consumption on Facebook. Advisor: Quattrociocchi, Dr. Walter. pp. 161. [IMT PhD Thesis]
|
Text
Schmidt_phdthesis.pdf - Published Version Download (25MB) | Preview |
Abstract
The advent of social media and microblogging platforms has radically changed the way we consume information and form opinions. Despite the importance given by the scientific community to these changes in news production and consumption, not much is certain about the spreading and consumption patterns through social media platforms. This thesis does an in-depth quantitative analysis of news consumption and polarization on Facebook, taking into account factors such as trust in news, confirmation bias and cognitive dissonance. First, we explore the anatomy of the English news by characterizing on a global scale the news consumption patterns of 376 million users over a time span of six years. Second, we compare the selective exposure and polarization of France, Germany, Italy and Spain (86M users), and present a model of selective exposure that considers trust in the emergence of communities. Finally, we analyze the polarization on the vaccination debate over time (2.6M users). Our findings show that confirmation bias and homophily are present in the users’ consumption of news, which leads to polarization and the creation of homogeneous communities. We also find that the preferences of users and news providers differ. By tracking how Facebook pages like each other and examining their geolocation, we find that users have a more cosmopolitan perspective of the information space than news providers. In addition, we devised two simple models of selective exposure that reproduce the observed connectivity patterns.
Item Type: | IMT PhD Thesis |
---|---|
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
PhD Course: | Complex networks |
Identification Number: | https://doi.org/10.6092/imtlucca/e-theses/254 |
NBN Number: | urn:nbn:it:imtlucca-27280 |
Date Deposited: | 12 Sep 2018 08:04 |
URI: | http://e-theses.imtlucca.it/id/eprint/254 |
Actions (login required, only for staff repository)
View Item |