Sentiment Analysis in Twitter: A SemEval Perspective
Sentiment Analysis in Twitter: A SemEval Perspective
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Twitter 中的情绪分析：SemEval 视角
DOI：
10.18653/v1/w16-0427
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Preslav Nakov
中科院分区：
文献类型：
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作者：
Preslav Nakov
最近社交媒体的兴起极大地促进了内容创作的民主化。Facebook、Twitter、Skype、Whatsapp和LiveJournal现在通常用于分享对周围世界任何事情的想法和看法。社交媒体内容的激增为研究公众舆论创造了新的机会，Twitter因其规模、代表性、讨论的主题多样性以及公众易于获取其信息而特别受欢迎。不幸的是，这方面的研究因缺乏用于系统培训、开发和测试的适当数据集和词汇而受到阻碍。虽然开发了一些Twitter特定的资源，但最初它们要么很小，要么是专有的，例如i-sieve语料库（Kouloumpis等人，2011年），仅为西班牙语创建，如塔斯语料库（Villena-Rom '
The recent rise of social media has greatly democratized content creation. Facebook, Twitter, Skype, Whatsapp and LiveJournal are now commonly used to share thoughts and opinions about anything in the surrounding world. This proliferation of social media content has created new opportunities to study public opinion, with Twitter being especially popular for research due to its scale, representativeness, variety of topics discussed, as well as ease of public access to its messages. Unfortunately, research in that direction was hindered by the unavailability of suitable datasets and lexicons for system training, development and testing. While some Twitter-specific resources were developed, initially they were either small and proprietary, such as the i-sieve corpus (Kouloumpis et al., 2011), were created only for Spanish like the TASS corpus (Villena-Rom´