Summary of Vocaltweets: Investigating Social Media Offensive Language Among Nigerian Musicians, by Sunday Oluyele et al.
VocalTweets: Investigating Social Media Offensive Language Among Nigerian Musicians
by Sunday Oluyele, Juwon Akingbade, Victor Akinode
First submitted to arxiv on: 10 Nov 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 This paper presents VocalTweets, a novel dataset comprising tweets from 12 prominent Nigerian musicians, classified as Normal or Offensive. The authors trained a model using HuggingFace’s base-Twitter-RoBERTa, achieving an F1 score of 74.5. To evaluate the generalizability of their dataset, they conducted cross-corpus experiments with the OLID dataset. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how musicians use social media to express themselves. Some musicians might say mean things online, while others might share supportive messages or take a stand on important issues. Researchers have studied how to detect mean language online before, but not specifically what musicians are saying. The authors created a special dataset called VocalTweets that includes tweets from famous Nigerian musicians and labeled them as normal or offensive. They used this dataset to train a model that can recognize mean language in tweets. |
Keywords
* Artificial intelligence * F1 score
