College of Computer and Information Technology, Henan Normal University, Xinxiang, China

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Abstract—Over the last few years, blogs (web logs) have gained massive popularity and have become one of the most important web social media, through which people can get and release information. Hot topic detection in blogs is most commonly used in analyzing network public opinion. A method of hot topic detection using n-gram model and hotness of topic evaluation is proposed in this paper. Our approach consists of three steps. First of all, keywords during a given time period are obtained by means of calculating word's weight, and hot keywords are collected by combining keywords. Secondly, based on hot keywords, hot keyword groups are extracted using n-gram model. In the third step, hot keyword groups are extracted and hot topics are detected. The hotness of hot topic is evaluated by the value of keywords’ weight, which is got in the second step. Evaluations on Chinese corpus show that when the size of n for n-gram is five, the proposed method is most effective.

Index Terms—n-gram model; blog; hot keyword; hot keyword group; hot topic.

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Cite: Xiaodong Wang, Juan Wang, "A Method of Hot Topic Detection in Blogs Using N-gram Model," Journal of Software vol. 8, no. 1, pp. 184-191, 2013.