The world of social media is a complex tapestry woven from text, images, videos, and sometimes audio. To unravel this intricate interplay, recent advancements in AI have introduced Large Multimodal Models (LMMs) like GPT-4V(ision). These models are adept at interpreting the nuanced interactions of various media forms, providing deeper insights into the messages conveyed on social platforms. Their prowess extends to diverse tasks, including sentiment analysis, hate speech detection, fake news identification, demographic inference, and political ideology detection.
“GPT-4V has the ability to construct a chain of thought based on tone as a basis for assessing fake news”
2.3.2 Tone and Language Analysis for Authenticity
Key Findings from the Research
- Sentiment Analysis: GPT-4V demonstrated its capability in multimodal sentiment analysis using image-text pairs from Twitter posts. By assessing whether these combinations conveyed positive, neutral, or negative sentiments, GPT-4V achieved an accuracy of 68.4% and 71.6% on different benchmark datasets. This performance highlights its ability to integrate information from multiple modalities to infer sentiments and emotions.
- Hate Speech Detection: In the realm of hate speech detection, GPT-4V was tested on challenging datasets, including HatefulMemes and 4chan’s posts. These datasets contain multimodal data like text and images designed to assess the model’s ability to detect hate speech and offensive content. GPT-4V’s task was to discern if the content was hateful or not, considering the complex interplay of multimodal elements.
Real-World Implications
GPT-4V’s exploration into social media analysis holds significant promise for enhancing our understanding of online content. It demonstrates a joint understanding of image-text pairs, contextual and cultural awareness, and extensive commonsense knowledge. However, challenges remain, such as struggling with multilingual social media content and adapting to the latest trends. Despite these hurdles, GPT-4V offers a glimpse into the future of AI’s role in computational social science and social media-related studies.
Conclusion
GPT-4V’s exploration in social media analysis marks a significant stride in understanding the multifaceted world of online communication. While it excels in interpreting complex multimodal content, challenges like multilingual comprehension and adapting to current trends highlight areas for future improvement. This study not only showcases the capabilities of AI in social media
Additional Information
- Publication Date: November 13, 2023
- Authors: Hanjia Lyu, Jinfa Huang, Daoan Zhang, Yongsheng Yu, Xinyi Mou, Jinsheng Pan, Zhengyuan Yang, Zhongyu Wei, Jiebo Luo
- Institutions: University of Rochester, Fudan University
- Link to Article: GPT-4V as a Social Media Analysis Engine.
