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

TL;DR

This paper introduces a semantic similarity-based method to measure the impact of strategic messages on online discourse, revealing the distribution of responses in social media discussions.

Contribution

The paper presents a novel technique leveraging semantic similarity and text embedding to quantify online discourse changes after strategic communications.

Findings

Heavy-tailed distribution of responses observed

Effective in analyzing environmental and climate change discussions

Provides a scalable way to evaluate message impact

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.