2 research outputs found
Combating Fake News on Social Media: A Framework, Review, and Future Opportunities
Social media platforms facilitate the sharing of a vast magnitude of information in split seconds among users. However, some false information is also widely spread, generally referred to as “fake news”. This can have major negative impacts on individuals and societies. Unfortunately, people are often not able to correctly identify fake news from truth. Therefore, there is an urgent need to find effective mechanisms to fight fake news on social media. To this end, this paper adapts the Straub Model of Security Action Cycle to the context of combating fake news on social media. It uses the adapted framework to classify the vast literature on fake news to action cycle phases (i.e., deterrence, prevention, detection, and mitigation/remedy). Based on a systematic and inter-disciplinary review of the relevant literature, we analyze the status and challenges in each stage of combating fake news, followed by introducing future research directions. These efforts allow the development of a holistic view of the research frontier on fighting fake news online. We conclude that this is a multidisciplinary issue; and as such, a collaborative effort from different fields is needed to effectively address this problem
Combating Misinformation in the Age of LLMs: Opportunities and Challenges
Misinformation such as fake news and rumors is a serious threat on
information ecosystems and public trust. The emergence of Large Language Models
(LLMs) has great potential to reshape the landscape of combating
misinformation. Generally, LLMs can be a double-edged sword in the fight. On
the one hand, LLMs bring promising opportunities for combating misinformation
due to their profound world knowledge and strong reasoning abilities. Thus, one
emergent question is: how to utilize LLMs to combat misinformation? On the
other hand, the critical challenge is that LLMs can be easily leveraged to
generate deceptive misinformation at scale. Then, another important question
is: how to combat LLM-generated misinformation? In this paper, we first
systematically review the history of combating misinformation before the advent
of LLMs. Then we illustrate the current efforts and present an outlook for
these two fundamental questions respectively. The goal of this survey paper is
to facilitate the progress of utilizing LLMs for fighting misinformation and
call for interdisciplinary efforts from different stakeholders for combating
LLM-generated misinformation.Comment: 9 pages for the main paper, 35 pages including 656 references, more
resources on "LLMs Meet Misinformation" are on the website:
https://llm-misinformation.github.io