OTSD: 58,000+ comments in Online Community for Target-level Sentiment Analysis

Abstract

Target-level sentiment analysis (TLSA) is to extract sentiments toward tar- gets in text. Since target-level sentiments play an important role in develop- ing marketing strategies for companies, several researchers have actively studied TLSA. However, existing datasets do not contain contextual information such as user, dependent-text. In this paper, we build and release Online community Target-level Sentiment analysis Dataset (OTSD) that contains 58,000+ online- community comments with rich contextual information: user ID, dependent-text, time and thumbs-up. With the real-world datasets, we observe that sentiments toward targets in text is closely related to not only text itself but also contextual information. To investigate the effectiveness of the contextual information, we build baseline models based on convolutional neural network that additionally utilize user and dependent-text information as the contextual information. Our experimental evaluations on the OTSD show that our baseline models outperform the state-of-the-art models that do not use the contextual information.