Positive and Negative Emotions on Social Media During Stay at Home Phase

Abstract

This research concerns with language patterns to express the emotional condition on social media. The research objective is to explain the use of language on Twitter to represent the positive and negative emotions from personal status. To enrich the information about the psychological condition through the linguistic pattern on social media, Linguistic Inquiry, and Word Count is used to build a strong relationship between linguistics pattern with the psychological conditions of emotions. This study's data are in written form, such as words, phrases, and sentences collected from Twitter from June up to August 2020 during the pandemic stay at home phase. There are seven users in some countries which use English as their first or second language. The result shows that status updates observed mostly cover positive emotions compared to negative ones. It reflects some extent that the positive emotions outweigh negative emotions in life in general. Therefore, positive biases in status updates are only established if they are more positive than emotional life or even social settings.