Twitter chirps for Syrian people: Sentiment analysis of tweets related to Syria Chemical Attack

Purpose: The sentiment analysis of tweets provides information about peoples' attitudes and perceptions towards an event. The current study showcases the role of Twitter in a crisis by analyzing the nature of tweets and the sentiments expressed by the Twitter-sphere during and after the Khan Shaykhun Syria Chemical Attack. Methodology: A total of 13,156 tweets posted in English on Twitter during the first 27 days of the attack were downloaded and considered for the study. The content analysis of the tweets was done manually, and accordingly, the sentiments of the tweets were highlighted through eight broader categories. Furthermore, to visualize the positive, negative, and neutral sentiments of the tweets, the Orange Data Mining Software, a powerful toolkit for machine learning, data mining, and data visualization, was used. VOSviewer (a software tool used for creating maps based on network data and for visualizing and exploring the maps) was also used to visualize the word frequency of the tweets. Findings: Twitter is primarily used for situational awareness and acts as an emotional, social support system by sharing sentiments. 35.71% of the tweets are associated with sharing news and information , with just 2.12% supporting the government. People mostly retweet the tweets that criticize the government, with an average retweet count of 15.84, followed by the ones evincing emotions (12.21). However, tweets that raise questions (3.32) and provide suggestions (2.51) fail to gain the attention of too many tweeter users, thus having less impact. People mostly like the tweets that support government and evince emotions, with such tweets on an average receiving 9.89 and 8.37 likes, respectively. Individuals post a large number of tweets (10,137; 77.05%), followed by news channels (1157; 8.79%) and organizations of varied nature (950; 7.22%). However, 912 (6.93%) tweets are posted by users of anonymous nature. Text and text with images form most tweets contributing to 8061 (61.27%) and 3137 (23.84%) of the total tweet count. However, none of the tweets contain video only, and just 3 (0.02%) tweets embed only images. Text-video and text-image formats are highly retweeted and liked. It is evident that 53.70% of the tweets (n = 7065) reflect negative sentiments, while 12.67% (n = 1667) emulate positive sentiments and, 33.63% (n = 4424) showcase a neutral perception about the attack. One can visualize the U.S.A. among the top tweeting countries with the highest percentage of positive sentiments, followed by Canada and Israel. Turkey outscores all the countries in terms of negative tweets, followed by Syria and U.K. However, in terms of neutral tweets, Germany ranks first, followed by Iran and Canada. The tweets pour mainly for the first few days, indicating the concern of users for the victims. Later on, a declining trend of tweets is witnessed. idlib, Syria, Syria chemical attack, and Assad are the leading words used more than a thousand times in the tweets. Research implications: The current study adds to the growing body of knowledge to the existing literature on Twitter and its use to narrowcast situational awareness during crisis episodes. One of the implications of the study is that the news agencies highly exploit the sharing side of Twitter during disasters by communicating realtime and unique information, create situational awareness, and connect to the digital audience. Twitter acts as an emotional outlet that facilitates the mining of condensed varied reactions towards an event to frame disaster response strategies and provides a sociological understanding of social media use during the crisis by the victims and viewers . Originality: The study represents the sentiments of the Twitter-sphere towards the Syria Chemical Attack.

Automated summary

The study explores the role of Twitter in crises through sentiment analysis, revealing people's attitudes and perceptions towards events. Twitter is primarily used for informational sharing and emotional support, with most tweets expressing negative sentiments but also showing positive and neutral views.