A proof-of-concept Tagalog Linguistic Inquiry and Word Count dictionary for positive and negative emotion developed for analyzing mixed language Twitter data from the Philippines and evaluated against human annotated sentiment for Twitter.
Development and Evaluation of Tagalog Linguistic Inquiry and Word Count (LIWC) Dictionaries for Negative and Positive Emotion
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As the use of online and social media increases globally, the need for sentiment analysis tools in multiple languages is critical in order to understand and analyze the vast amount of data that may contain users’ feelings, perceptions, and beliefs. Users from different countries convey their messages in various languages, which may convey different sentiments and cultural connotations. Developing non-English sentiment analysis tools can ensure that data is not lost due to language. A proof-of-concept Tagalog Linguistic Inquiry and Word Count (LIWC) dictionary for positive and negative emotion was developed for use in analyzing mixed language Twitter data from the Philippines and evaluated against human annotated sentiment for Twitter, referred to as groundtruth.