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即时通讯服务中短句情绪辨识之研究:基于情绪座标与轨迹

【中文摘要】:在即时通讯

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软体和聊天室中,文字和情绪往往有正向的相关性,随着情绪的起伏,会影响到使用者的用字遣词,在商业谈判与交友等应用中,能否準确辨识对方的情绪经常是成败的关键,但文字不如

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面部表情一样能轻易地辨识情绪,一句平淡无奇的短句,在某些谈话背景中可能隐藏着波涛汹涌的情绪起伏,单纯从字面上的意义无法精準地推论当下使用者的情绪。
因此在本篇论文中,试着使用情绪座标与向量来记录情绪轨迹,将会比『开心』、『生气』、『难过』等标籤更精準地表达情绪变化,除此之外,每当计算一则短文的情绪向量时,更会考量到前文的情绪,来决定该则短文的情绪向量,能够有效避免仅从单一则短文的字面意思来辨识时容易产生的误判,最后计算得到的情绪轨迹可以用于分析情绪成份,并比较即时通讯服务双方的情绪相似度。
【英文摘要】:In most of instant messenger services and chat rooms, the texts and the users’ emotions tend to show a positive correlation. This means that the users’ emotions predominantly affect their wording. While the users were having conversations within some applications such as business negotiations and dating services, the ability to accurately identify emotions

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of other party is the key to success. However, to recognize emotions from facial expressions is easier than from the textual contents. Strong mood swings may exist in a seemingly simple sentence in some context, so it is not sufficient to recognize the user’s emotion based only on the literal meaning of their words.
In this study, I try to make use of emotion coordinates and vectors to record the trajectories of emotions. Recognizing and recording the move of emotions this way is more accurate than using basic tags as simple as “Happy”, “Angry”, “Sad” or other labels. Moreover, when calculating an emotion vector of a short message, one can take into account of the previous emotion contexts to determine the vector of the current emotion. This way, we can avoid misjudgment based only on the literal meaning. Emotion trajectories last calculated can be used to analyze the elements of emotions and compare the emotion of the users in instant messenger services.
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  • 来源:中山大学;作者:陈致豪
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