CORPUS LINGUISTIC STUDY OF TWEETS USING #CHARLIEHEBDO HASHTAG

Autor: Nugraha, Intan Siti, Sujatna, Eva Tuckyta S., Mahdi, Sutiono
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: JALL (Journal of Applied Linguistics and Literacy); Vol 5, No 1 (2021); 54-70
ISSN: 2598-8530
Popis: Hashtags of #CharlieHebdo becomes trending in Twitter when a knife attack incident happened in front of former Charlie Hebdo magazine’s office on 25 September 2020. If #JeSuisCharlie was used to show empathy and support for the victim and freedom of speech value, #CharlieHebdo still remains question on what topics around the Twitter discussion using the hashtag. Thus, using corpus linguistic analysis method, which are keyword and concordance analysis, this study aims to investigate the significant topic of corpus containing #CharlieHebdo. The tweet corpus which contains 8.604 tweets and retweets and words in total are 177.352 tokens (words) was constructed from the tweets scrapped by the researcher using Python and Twitter API. The result of analysis shows that there are at least 13 categories of keywords which indicate significant topics of the tweet corpus. They are place, attacker, act, weapon, religion/belief, motive, victims, figures, emotion evoked, law enforcement and other topics.
Databáze: OpenAIRE