| Summary: | 碩士 === 國立清華大學 === 資訊系統與應用研究所 === 103 === The ubiquity of internet and permanent growth in popularity of Microblogging
Social Networks over the past years, has also led to a significant increase in the
data uploaded by users to these Microblog sites. However the generated data is
dynamic by nature, tied to temporal conditions and the subjectivity of its users.
Everyday life experiences, discussions or events have a direct impact on the behaviors
reflected in social networks. It is therefore of great importance to asses the
impact these interactions are having over a social group. An alternative to answer
this is determining how influential a topic is according to the behavior presented
on a social network over time. It is then necessary to find and develop methods
that can leverage towards this task. This work combines three fields relevant to
this kind of data utilization: topic identification, emotion classification and influence
determination. Once a topic is identified we first classify it as time specific or
long term, then posts relevant to the topic are collected and each one is assigned an
emotion label. After processing the stream of posts to favor a time based analysis
we propose an Influence Value score which will be given to each topic based on its
lifespan, emotion transition and reach in order to quantify how influential a topic is
over a social group, specifically from events detected on twitter. In other words we
summarize the emotional response towards an event and combine it with temporal
variables to determine how influential it is over a social group.
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