分析西班牙媒体评论区的舆论，发现负面情绪主导且热点集中于社会政治议题。
Exploring the topics, sentiments and hate speech in the Spanish information environment
- 用BERTopic自动提取81个话题，结合LLM人工命名并归类为9大类。
- 62.7%内容负面，仅3.98%含仇恨言论，但涉及性别、疫情等话题毒性高。
- 适合关注网络舆情、媒体影响与社会极化的研究者和从业者参考。
在数字时代，互联网与社交媒体虽改变沟通方式，但也加速了仇恨言论与虚假信息传播，引发极端化、两极分化与网络毒性。媒体在此过程中扮演关键角色。本研究分析2021年1月五家西班牙媒体（La Vanguardia、ABC、El País、El Mundo、20 Minutos）新闻下的337,807条公众评论（网站留言与推文），这些评论此前由专家按原创流程标注为不同类型的仇恨言论。现将其重新分类为三类情感（负面、中性、正面）及主要话题。采用BERTopic无监督框架提取出81个话题，借助大型语言模型（LLMs）人工命名，并归入九个主类别。结果显示，讨论最频繁的是社会议题（22.22%）、表达与俚语（20.35%）和政治议题（11.80%）。内容以负面（62.7%）和中性（28.57%）为主，正面仅占8.73%。有毒叙事主要关联对话表达、性别、女权主义及新冠疫情。尽管仇恨言论整体占比低（3.98%），但针对社会与政治话题的在线回应仍表现出高度毒性。
原文摘要 · Abstract (English)
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 País, 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.
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