Thesis subject

Identifying Trends in Social Network Data: A case study on extended reality hardware (BSc/MSc)

This project investigates XR hardware trends using social media data from Twitter/X. Objectives include analysing trends and sentiment towards XR headsets (e.g., Apple Vision Pro), uncovering demographic insights, etc.

Short description

The rapid emergence of various XR headsets, including the new Apple Vision Pro and Meta Quest 3, has transformed the landscape of immersive technology. This project investigates social media data, specifically from Twitter/X, to analyse trends in XR hardware. By investigating user discussions, sentiment, and engagement, the aim of the study is to identify the most influential factors driving XR adoption and preferences. The insights garnered will provide valuable information on consumer behavior and technological advancements, helping stakeholders make informed decisions in the XR market. This investigation into social media trends will involve using data analytics (e.g., natural language processing) to identify patterns and insights from user-generated content. Additionally, the project will explore how different demographics engage with various XR devices on social media. This project is suitable for students with an interest in data science, social media analytics, natural language processing.

Objectives and Tasks

  • Conduct a detailed literature review on existing XR hardware and trends in the market.
  • Design a comprehensive framework for analysing social media data related to XR hardware.
  • Collect quantitative and qualitative feedback on the design and suitability for Web 4.0 education.
  • Identify and analyse the most discussed XR headsets, including the Apple Vision Pro, on Twitter/X to understand current market trends and user preferences.
  • Conduct sentiment analysis on social media posts to gauge public perception and satisfaction with various XR headsets, highlighting key factors that influence user opinions.

Literature

  • Analyzing Social Networks Using R, S.P. Borgatti, Sage Publishing, ISBN: 9781529722475;

Requirements

  • Courses: Data Science Concepts (INF-34306) (Optional)
  • Required skills/knowledge: Python or R experience, General interest in XR and Data Science

Key words: Data Science, eXtended Realities, Information technology,

Contact person(s)

Will Hurst (will.hurst@wur.nl)