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  • Research for Reasoning Occupation of Users Using Time Posted to Microblogs

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Research is being conducted on technology to get users' reactions to specific topics in microblogs. It is necessary to know the users' characteristics in order to effectively utilize microblogs as social sensors. However, it cannot understand the users' characteristics, because user attributes are not often to the public in microblogs. For this reason, research on estimating user attributes in microblogs has been drawing attention. However, existing methods, which merely focus on the description contents in microblogs, do not take advantage of the characteristics in microblogs that transmit in real time to estimate users' attributes. This research proposes a method for classifying the users according to number of posts per unit time and estimating the occupation attributes by description contents, lifestyle and time zone of posts. Our demonstration experiments verify usability of the proposed method by comparing the existing methods of estimating merely using description contents with the proposed method of estimating using description contents and temporal characteristics.


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