Using Semantic Similarity and Text Embedding to Measure the Social Media Echo of Strategic Communications

2023/03/29 by Tristan J. B. Cann, Ben Dennes, Cann, Tristan J. B. +7 · 1 citation
Physics and Astronomy · Social Sciences · #Complex Network Analysis Techniques #Computation and Language (cs.CL) #FOS: Computer and information sciences #Opinion Dynamics and Social Influence #Social Media and Politics #Social and Information Networks (cs.SI)

paper · pdf · doi:10.48550/arxiv.2303.16694

openalex publication_date 2023/03/29 · openalex created_date 2023/04/05 · openalex updated_date 2026/07/28

Abstract

Online discourse covers a wide range of topics and many actors tailor their content to impact online discussions through carefully crafted messages and targeted campaigns. Yet the scale and diversity of online media content make it difficult to evaluate the impact of a particular message. In this paper, we present a new technique that leverages semantic similarity to quantify the change in the discussion after a particular message has been published. We use a set of press releases from environmental organisations and tweets from the climate change debate to show that our novel approach reveals a heavy-tailed distribution of response in online discourse to strategic communications.

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