Examining regional variations in effective posts on X (Twitter) during the COVID-19 pandemic

Abstract

Social media platforms play a significant role in disseminating information. The effectiveness of posts published on such platforms is often measured by the extent to which those posts are reshared — something that can be shaped by the regional social and cultural context. This study examines regional variations in effective posts (formerly tweets) published on X (formerly known as Twitter) during the initial phase of the COVID-19 pandemic, focusing on California’s two largest cities: Los Angeles and San Diego. By analysing a large dataset comprising the top 5,000 most reposted (formerly retweeted) posts from users in both cities, gathered between 17th March and 11th April, 2020, the research aims to identify key posters and content characteristics associated with higher repost rates. Employing techniques such as topic modelling and sentiment analysis, this study transforms unstructured text data into quantitative metrics in order to explore the relationship between content metrics and the number of reposts. The findings highlight the significant influence of local figures in shaping user engagement with shared posts spanning diverse topics and sentiments. These insights have significant implications for marketers, emphasising the importance of understanding local influencers, post topics and sentiment in geo-tagged posts. In regions with diverse populations, businesses can develop strategies to collaborate with local influencers and actively involve community leaders from various cultural backgrounds. By doing so, they facilitate the dissemination of trustworthy information and enhance engagement with culturally diverse audiences. Ultimately, this approach enables marketers to transform regional disparities into strategic advantages, fostering more effective communication and engagement on social media.