| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Outline of Final Research Achievements |
We studied a method for extracting communities (i.e., the users that have similar characteristics) and the terms used in the communities simultaneously, based on the assumption that similar communities use similar terms. We focus on the profiles written by the users on Twitter, and we developed a system that extract the frequently-used terms by the users with the profiles that include the given query word. We also developed a method for word distributed representations that reflect the co-occurrence of the words in profiles and tweets, and cluster users and tweets based on the learned vector representation.
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