Mining ideological discourse on Twitter: The case of extremism in Arabic

Extremism has been a problematic term to define and suggests different and opposing meanings. This study explores how Twitter users conceptualize extremism in Arabic and express their opinions/arguments to construct the term. A corpus of tweets was collected from Twitter API using the word ‘تطرف أو متطرف’ in Arabic for extremist/extremism. A topic modeling algorithm was then applied to the dataset to uncover latent associated concepts underlying extremism, followed by a critical discourse analysis using Van Dijk’s Sociocognitive approach. The discursive and linguistic strategies used by Twitter users to support and justify their views of extremism were examined. The findings demonstrate an ideological influence that controls the concept of extremism, keeping it open to manipulation to serve shared interests and goals. Arab users of Twitter use extremism to promote their groups’ positive schema against others-negative schema.

Tags: critical discourse studies, discourse and ideology, extremism on Twitter, text analytics, text mining