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http://hdl.handle.net/11375/30045
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DC Field | Value | Language |
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dc.contributor.advisor | Yuan, Yufei | - |
dc.contributor.advisor | Turel, Ofir | - |
dc.contributor.author | Nasery, Mona | - |
dc.date.accessioned | 2024-08-14T20:53:10Z | - |
dc.date.available | 2024-08-14T20:53:10Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://hdl.handle.net/11375/30045 | - |
dc.description.abstract | Social media platforms facilitate the spread of a large volume of information in split seconds. However, some false information is widely spread, generally called “fake news”. This can have significant negative impacts on individuals and societies. Thus, there is an urgent need to find effective mechanisms to combat fake news on social media. The first step to address this problem is to understand fake news clearly. To this end, this research first provides an overview of the fake news lifecycle and different types of false information. This dissertation includes two primary studies. The first study aims to understand various kinds of false information on social media, focusing on X. We analyzed the spread dynamics of different types of false tweets and user behaviour towards each type using advanced data analytics and NLP methods. Finally, we examined whether and how users’ responses affect the spread of false tweets. This study is important from several aspects. First, considering the rapid spread of fake news on social media, only a tiny fraction can be flagged by fact-checkers. Understanding the spread dynamics of diverse types of false information helps decide what kinds of false content to fact-check first. Second, analyzing users’ conversations provides insights into users’ behaviour. It shows what users think and how they react to a piece of information, which helps develop more efficient fake news detection and classification tools. The second study aims to provide a comprehensive approach to combat fake news on social media. We adopt the Straub Model of Security Action Cycle to the context of fighting fake news on social media. We use the framework to classify the vast literature on fake news into action cycle phases (deterrence, prevention, detection, and mitigation). Based on a systematic and inter-disciplinary literature review, we analyze the status and challenges in each stage of combating fake news and introduce future research directions. These efforts allow the development of a holistic view of the research frontier on fighting fake news online. | en_US |
dc.language.iso | en | en_US |
dc.title | Fake News on Social Media: From Fake News Lifecycle to Fake News Combat Cycle | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Business Administration | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Nasery_Mona_FinalSubmission202405_PhD.pdf | 6.86 MB | Adobe PDF | View/Open |
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