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Exploring the topics, sentiments and hate speech in the Spanish information environment

arXiv 2409.12658 ↗First posted 19 Sep 2024cs.CLcited by 0

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Abstract (arXiv)

In the digital era, the internet and social media have transformed communication but have also facilitated the spread of hate speech and disinformation, leading to radicalization, polarization, and toxicity. This is especially concerning for media outlets due to their significant role in shaping public discourse. This study examines the topics, sentiments, and hate prevalence in 337,807 response messages (website comments and tweets) to news from five Spanish media outlets (La Vanguardia, ABC, El Pa'is, El Mundo, and 20 Minutos) in January 2021. These public reactions were originally labeled as distinct types of hate by experts following an original procedure, and they are now classified into three sentiment values (negative, neutral, or positive) and main topics. The BERTopic unsupervised framework was used to extract 81 topics, manually named with the help of Large Language Models (LLMs) and grouped into nine primary categories. Results show social issues (22.22%), expressions and slang (20.35%), and political issues (11.80%) as the most discussed. Content is mainly negative (62.7%) and neutral (28.57%), with low positivity (8.73%). Toxic narratives relate to conversation expressions, gender, feminism, and COVID-19. Despite low levels of hate speech (3.98%), the study confirms high toxicity in online responses to social and political topics.

Key facts. No citing papers in the map yet (data through 13 Oct 2026). Builds on 11 of its 47 references that are in the map. First posted on arXiv 19 Sep 2024.

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References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,304
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,322
  3. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,986
  4. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,467
  5. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 792
  6. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 416
  7. 2020BERTweet: A pre-trained language model for English Tweetscited by 346
  8. 2022TweetNLP: Cutting-Edge Natural Language Processing for Social Mediacited by 71
  9. 2022Propaganda and Misinformation on Facebook and Twitter during the Russian Invasion of Ukrainecited by 10
  10. 2020Spotting political social bots in Twitter: A use case of the 2019 Spanish general electioncited by 6
  11. 2024A Big Data Architecture for Early Identification and Categorization of Dark Web Sitescited by 1

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