Social sensing and sentiment analysis: Using social media as useful information source

Social sensing and sentiment analysis: Using social media as useful information source
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社会感知和情绪分析:使用社交媒体作为有用的信息源

DOI:
10.1109/sst.2017.8188714
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发表时间:
2017
期刊:
2017 International Conference on Smart Systems and Technologies (SST)
影响因子:
--
通讯作者:
Michela Fazzolari
Michela Fazzolari
中科院分区:
--
文献类型:
--
作者:
Pietro Ducange;Michela Fazzolari

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在本文中,我们简要介绍了社会感知和情感分析范式。第一个是关于一般框架,其中来自社交媒体的信息,特别是来自在线社交网络(OSN)的信息,可以用于挖掘有用的知识,以在几个现实世界的应用程序中加以利用。事实上,人们在OSN上共享的所有元素(文本、链接、位置、图像等)都可以被认为是社交或人类传感器的信息内容。这些内容可用于多种情况,例如实时监控、预测和识别事件,以及研究人们在OSN上发布的文本中分享的观点、情感、情绪和情绪。更具体的框架,其中来自社交网络的信息被采用来检测极性(例如,积极的、中性的或消极的)与文本相关联的情感被标记为情感分析。在这项工作中,我们还展示了社会感知和情感分析的两个实际应用。
In this paper, we briefly introduce the social sensing and sentiment analysis paradigms. The first one regards the general framework in which information coming from social media, and in particular from On Line Social Networks (OSNs), may be used for mining useful knowledge to be exploited in several real-world applications. Indeed, all the elements that people share on OSNs (texts, links, positions, images and so on) may be considered as the informative content of social or human sensors. This content may be used in several contexts such as real-time monitoring, prediction and identification of events, and for studying opinions, sentiments, moods and emotions that people share in the texts published on OSNs. The more specific framework, in which information coming from social networks are adopted for detecting the polarity (e.g., positive, neutral, or negative) of the sentiment associated with a text, is labelled as sentiment analysis. In this work, we also show two real-world applications of both social sensing and sentiment analysis.
DOI: --
发表时间: 2014
期刊: Journal of management science
影响因子: --
作者:
อนิรุธ สืบสิงห์
通讯作者: อนิรุธ สืบสิงห์