Identify, Inspect and Intervene Multimodal Fake News
Fake news refers to intentionally and verifiably false stories created to manipulate people’s perceptions of reality. The concept of fake news is not new and has marked its presence dating back to AD 1475, affecting the citizens of Italy on eastern Sunday to the COVID-19 pandemic in 2020. Fake news has gained traction among audiences, created a buzz online, and faced repercussions offline. For instance, intruding hyperbolized fake articles into political campaigns or health and climate studies is havoc. In addition, the proliferation of fabricated stories has played a crucial role in inflaming or suppressing a social event. In conclusion, fake news is destructive and can lead to hatred against religion, politics, celebrities or organizations, resulting in riots/protests or even death. The massive growth in the proliferation of fake news online might result from numerous technological advancements. Fake news seems to be the permanent reality, with social media being a primary conduit for its creation and dissemination. Despite the difficulty in identifying, tracking, and controlling unreliable content, there must be an effort to halt its expansion. Our research endeavors contribute to tackling various aspects of fake news, encompassing identification, inspection, and intervention. The premise of our thesis is firmly placed at the point where we analyze multiple facets of user-generated content produced online in the form of text and visuals to investigate the field of fake news. First, we focus on devising different methods to Identify, a.k.a. detect fake news online, by extracting different feature sets from the given information. By designing foundational detection mechanisms, our work accelerates research innovations. Second, our research closely Inspects the fake stories from two perspectives. First, from the information point of view, one can inspect fabricated content to identify the patterns of false reports disseminating over the web, the modality used to create the fabricated content and the platform used for dissemination. Next, from the model point of view, we inspect detection mechanisms used in prior work and their generalizability to other datasets. The thesis also suggests Intervention techniques to help internet users broaden their comprehension of fake news. We discuss potential practical implications for social media platform owners and policymakers.
