理解社交媒体上对气候变化的态度
Understanding Opinions Towards Climate Change on Social Media
AI总结：
本文通过分析2006至2019年间1360万条推文，构建时序图并利用Louvain算法和自然语言处理方法，研究COP事件对社交媒体上气候变化讨论社区结构和情感主题演变的影响，为提升公众气候意识提供依据。
摘要：
Twitter（现称X）等社交媒体平台已经彻底改变了公众参与重要社会和政治议题的方式。近年来，社交媒体上的气候变化讨论成为政治极化和错误信息传播的催化剂。在这项工作中，我们旨在理解现实世界事件如何影响个人在社交媒体上对气候变化相关话题的态度。为此，我们提取并分析了一个包含2006年至2019年间360万用户发送的1360万条推文的数据集。然后，我们从用户-用户提及网络中构建了一个时序图，并利用Louvain社区检测算法分析气候变化缔约方大会（COP）事件前后社区结构的变化。接下来，我们还应用自然语言处理文献中的工具对推文进行情感分析和主题建模。我们的工作是理解COP事件前后支持气候变化社区演变的第一步。回答这些问题有助于我们理解如何提高人们对气候变化的认识，从而有望呼吁更多人加入到减缓气候变化的合作努力中来。
英文摘要：
Social media platforms such as Twitter (now known as X) have revolutionized how the public engage with important societal and political topics. Recently, climate change discussions on social media became a catalyst for political polarization and the spreading of misinformation. In this work, we aim to understand how real world events influence the opinions of individuals towards climate change related topics on social media. To this end, we extracted and analyzed a dataset of 13.6 millions tweets sent by 3.6 million users from 2006 to 2019. Then, we construct a temporal graph from the user-user mentions network and utilize the Louvain community detection algorithm to analyze the changes in community structure around Conference of the Parties on Climate Change~(COP) events. Next, we also apply tools from the Natural Language Processing literature to perform sentiment analysis and topic modeling on the tweets. Our work acts as a first step towards understanding the evolution of pro-climate change communities around COP events. Answering these questions helps us understand how to raise people's awareness towards climate change thus hopefully calling on more individuals to join the collaborative effort in slowing down climate change.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
