[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 25 March – Álvaro Figueira – Machine Learning to Identify HE Institutions’ Social Media Publication Strategies

Faculdade de Ciências

Universidade do Porto, Portugal

A Machine Learning Approach to Identify Higher Education Institutions’ Social Media Publication Strategies

Abstract

In the competitive landscape of higher education, institutions use
international rankings to secure funding, attract talent, and enhance
their global reputation. At the same time, they leverage social media
to boost recognition and engagement. This study examines the
relationship between Higher Education Institutions’ (HEIs) rankings
and their social media posting strategies. Analyzing tweets from 18
HEIs in a consolidated ranking system, we identified four distinct
clusters based on posting strategies, aligning with three ranking
tiers: high, moderate, or low. Posts were categorized into five
topics—engagement, research, image, society, and education—and an LSTM
model successfully predicted social media activity, revealing clear
patterns. Our findings suggest a connection between social media
engagement and HEI prestige.

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