Micro-opinion Sentiment Intensity Analysis and Summarization in Online Videos

Amir Zadeh
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引用次数: 26

Abstract

There has been substantial progress in the field of text based sentiment analysis but little effort has been made to incorporate other modalities. Previous work in sentiment analysis has shown that using multimodal data yields to more accurate models of sentiment. Efforts have been made towards expressing sentiment as a spectrum of intensity rather than just positive or negative. Such models are useful not only for detection of positivity or negativity, but also giving out a score of how positive or negative a statement is. Based on the state of the art studies in sentiment analysis, prediction in terms of sentiment score is still far from accurate, even in large datasets [27]. Another challenge in sentiment analysis is dealing with small segments or micro opinions as they carry less context than large segments thus making analysis of the sentiment harder. This paper presents a Ph.D. thesis shaped towards comprehensive studies in multimodal micro-opinion sentiment intensity analysis.
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网络视频中的微意见情绪强度分析与总结
在基于文本的情感分析领域已经取得了实质性进展,但很少努力纳入其他模式。先前在情绪分析方面的工作表明,使用多模态数据可以产生更准确的情绪模型。人们努力将情绪表达为一系列的强度,而不仅仅是积极或消极。这些模型不仅对检测积极或消极有用,而且还对陈述的积极或消极程度进行评分。基于情感分析的最新研究,即使在大型数据集中,基于情感得分的预测仍然远远不够准确[27]。情绪分析的另一个挑战是处理小片段或微观点,因为它们比大片段具有更少的背景,从而使情绪分析变得更加困难。本文提出了一篇针对多模态微意见情绪强度分析的综合研究的博士论文。
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