Tunisia Twitter Data

Following the 2011 Tunisian Revolution, Tunisia is widely recognized as an Arab-Spring success story. With campaigns for civil resistance against corruption and civil oppression, the Tunisian Revolution consisted of mass demonstrations that ultimately inspired presidential elections and other democratic reforms across the nation, and a wave of similar protests across the Arab world. In 2021, amid ongoing demonstrations against government dysfunction and corruption, Tunsian President Kais Saied suspended the parliament, replaced the Prime Minister, and began drafting constitutional amendments which reversed nearly a decade of democratic reforms. As freedoms of speech and expression, the right to organize, and many local media outlets have been oppressed, Tunisians have taken to platforms like Twitter to speak truthfully. Thus, CS4624 Team 21 was focused on identifying and analyzing Twitter data relating to democracy, political reforms, and public sentiment in Tunisia since 2020. Team 21 primarily worked with clients Drs. Kavanaugh, Sheetz, Miller, and Farag to analyze Tunisian Twitter data collected by a larger research team in collaboration with Virginia Tech’s (VT) University Libraries. The team handled Twitter data previously collected at VT, as well as more recent data that extends the previous collection. After preprocessing all data to add sentiment scores and filter by English language, the team analyzed the cleaned collection of tweets for key terms and hashtags provided by their clients. The team determined counts for each keyword, extracted a list of URLs used in the tweets, and created visualizations of topic models to visualize monthly keyword and sentiment trends in the relevant timeline. Lastly, the team converted the cleaned tweet collection to consistent JSONL format determined via consultation with the client for eventual integration into the VT library repository. Ultimately, the team expects their project to revitalize research at VT related to Twitter data, inspire new publications about Tunisia based on Twitter data, and lead to a greater understanding of public sentiment about political reforms in Tunisia.