Project Abstract

Motivation and Background: The exponential growth of artificial intelligence (AI) technologies and their broad discourse on social media platforms, particularly Twitter, highlight the platform’s role as a critical hub for knowledge sharing and networking among AI enthusiasts. Understanding how AI-related content, specifically tweets using hashtags like #aitools, is disseminated can significantly impact content visibility, community engagement, and outreach.Proposition of the Research: This study uniquely positions itself by investigating the engagement dynamics of tweets related to AI tools using the #aitools hashtag and associated tags. The main aim is to analyze the factors influencing the engagement of these tweets, thereby guiding content optimization strategies for a more informed AI discourse.Methods Employed: The research employs a quantitative approach using the Twitter API to collect and analyze data on tweets with #aitools and related hashtags. Key metrics such as retweet rates, multimedia inclusion, timing of tweets, and user characteristics (e.g., number of followers) are examined to understand their impact on tweet engagement.Main Findings (Expected): The project anticipates discovering significant trends showing that optimal timing, multimedia content, and influential user profiles enhance tweet engagement. These insights are expected to help in crafting strategies that increase content visibility and interaction within the AI community on Twitter.Conclusion / Contribution: The expected contribution of this research is to provide a deeper understanding of the dynamics influencing social media engagement within the AI domain. By identifying effective strategies for tweet dissemination, the project aims to enhance the spread and impact of AI-related content, thus enriching the digital conversation around artificial intelligence on platforms like Twitter.

Keywords: Twitter Engagement, Artificial Intelligence, Social Media Analytics

 Conference Details

Session: Presentation Stream 11 at Presentation Slot 5

Location: College 127 at Tuesday 7th 13:30 – 17:00

Markers: Nicholas Micallef, Alec Critten (GTA)

Course: MSc Computer Science, Masters PG

Future Plans: I’m looking for work