Shigeyuki Sakaki


Corpus for Customer Purchase Behavior Prediction in Social Media
Shigeyuki Sakaki | Francine Chen | Mandy Korpusik | Yan-Ying Chen
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Many people post about their daily life on social media. These posts may include information about the purchase activity of people, and insights useful to companies can be derived from them: e.g. profile information of a user who mentioned something about their product. As a further advanced analysis, we consider extracting users who are likely to buy a product from the set of users who mentioned that the product is attractive. In this paper, we report our methodology for building a corpus for Twitter user purchase behavior prediction. First, we collected Twitter users who posted a want phrase + product name: e.g. “want a Xperia” as candidate want users, and also candidate bought users in the same way. Then, we asked an annotator to judge whether a candidate user actually bought a product. We also annotated whether tweets randomly sampled from want/bought user timelines are relevant or not to purchase. In this annotation, 58% of want user tweets and 35% of bought user tweets were annotated as relevant. Our data indicate that information embedded in timeline tweets can be used to predict purchase behavior of tweeted products.


A Weighted Combination of Text and Image Classifiers for User Gender Inference
Tomoki Taniguchi | Shigeyuki Sakaki | Ryosuke Shigenaka | Yukihiro Tsuboshita | Tomoko Ohkuma
Proceedings of the Fourth Workshop on Vision and Language


TeamX: A Sentiment Analyzer with Enhanced Lexicon Mapping and Weighting Scheme for Unbalanced Data
Yasuhide Miura | Shigeyuki Sakaki | Keigo Hattori | Tomoko Ohkuma
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

Twitter User Gender Inference Using Combined Analysis of Text and Image Processing
Shigeyuki Sakaki | Yasuhide Miura | Xiaojun Ma | Keigo Hattori | Tomoko Ohkuma
Proceedings of the Third Workshop on Vision and Language