Summary of Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames, by Keith Burghardt et al.
Large Language Models Reveal Information Operation Goals, Tactics, and Narrative Frames
by Keith Burghardt, Kai Chen, Kristina Lerman
First submitted to arxiv on: 6 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach is proposed in this paper to mitigate limitations in understanding influence campaigns by leveraging large language models (LLMs). Specifically, GPT-3.5 is used as a case-study for coordinated campaign annotation. The authors utilize GPT-3.5 to scrutinize 126 identified information operations spanning over a decade, demonstrating close agreement between LLM and ground truth descriptions using various metrics. Additionally, the paper extracts coordinated campaigns from two large multilingual datasets discussing the 2022 French election and 2023 Balikaran Philippine-U.S. military exercise in 2023. The GPT-3.5 is used to analyze posts related to specific concerns, extracting goals, tactics, and narrative frames before and after critical events. This research highlights the potential of LLMs to provide a more complete picture of information campaigns compared to previous methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us understand how fake news and misinformation can spread quickly online. The researchers use special language models called GPT-3.5 to analyze messages from many different sources. They want to see if these models can help us figure out what’s going on behind the scenes of these “influence campaigns”. By looking at old messages, they found that the language models are pretty good at matching what people meant when they wrote something. The authors also looked at big groups of posts talking about important events like elections and military exercises. They used GPT-3.5 to see if it could understand what these groups were trying to do and how they were doing it. This research shows that language models can be helpful in understanding online manipulation. |
Keywords
» Artificial intelligence » Gpt
