Detecting Social Problems in Online Content: A Preface to the International Workshop

机译：检测在线内容中的社会问题：国际研讨会的序言

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This workshop was dedicated to discussing the latest development in detecting a broad range of social issues in online content, from inequalities expressed in texts (hate speech, prejudice, divisive/uncivil messages, political bias and racism etc.), to social polarization based on user views and sentiment. With proliferation of social media, such content is increasingly impactful, while its detection at scale presents a huge methodological challenge. The workshop participants shared their research experience by reflecting both on advantages and limitations of new automated and mixed research methods of text analysis they had used for processing and analysing such content. The workshop was held for the first time at INSCI'2018.

机译：该讲习班致力于讨论检测在线内容中广泛的社会问题的最新进展，从文本中表达的不平等（仇恨言论，偏见，分裂/不文明消息，政治偏见和种族主义等），到基于用户的观点和观点。随着社交媒体的普及，此类内容越来越具有影响力，而其大规模检测则带来了巨大的方法挑战。研讨会的参加者分享了他们的研究经验，同时回顾了他们用于处理和分析此类内容的新型自动和混合文本分析研究方法的优点和局限性。该研讨会是在INSCI'2018上首次举行的。

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《International Workshops on Internet Science》|2018年|2-5|共4页
会议地点 St. Petersburg(RU)
作者
Olessia Koltsova; Svetlana Bodrunova;
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作者单位

National Research University Higher School of Economics 16 Soyuza Pechatnkov 190005 St. Petersburg Russia;

St. Petersburg State University Universitetskaya nab. 7/9 199034 St. Petersburg Russia;

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Problematic content; Online data; Machine learning; Text clustering; Big social data; Limitations;

机译：有问题的内容；在线数据；机器学习；文本聚类；大社交数据；局限性;

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Detecting Social Problems in Online Content: A Preface to the International Workshop

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