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

Tristan J. B. Cann; Ben Dennes; Travis Coan; Saffron O'Neill; Hywel T. P. Williams

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arXiv · 2303.16694

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

Tristan J. B. Cann·Ben Dennes·Travis Coan·Saffron O'Neill·Hywel T. P. Williams

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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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Tristan J. B. Cann, Ben Dennes, Travis Coan, Saffron O'Neill, Hywel T. P. Williams. 2023-03-29. Using Semantic Similarity and Text Embedding to Measure the Social Media Echo of Strategic Communications. https://arxiv.org/abs/2303.16694

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