Summary of Identification Of Emotions on Twitter During the 2022 Electoral Process in Colombia, by Juan Jose Iguaran Fernandez et al.
Identification of emotions on Twitter during the 2022 electoral process in Colombia
by Juan Jose Iguaran Fernandez, Juan Manuel Perez, German Rosati
First submitted to arxiv on: 9 Jul 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 study presents a small corpus of tweets in Spanish related to the 2022 Colombian presidential elections, manually labeled with emotions using a fine-grained taxonomy. The paper aims to fill the gap in emotion detection in Spanish, particularly in Colombian Spanish, which lacks public resources for opinion mining. State-of-the-art BERT models and GPT-3.5 are employed for classification experiments in few-shot learning settings. This research contributes to the analysis of social phenomena on Twitter, providing valuable insights into people’s subjective responses to political events. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A group of researchers created a special collection of tweets about the 2022 Colombian presidential election. They added words like “happy”, “sad”, or “angry” to each tweet to help machines understand how people felt about the election. This is important because it can give us clues about what people are thinking and feeling when they talk about politics. The team used special computer models to try to predict how people would feel based on their tweets, and they compared these results with a newer model that can learn quickly. They shared all of this information so other researchers can use it too. |
Keywords
» Artificial intelligence » Bert » Classification » Few shot » Gpt
