Forecasting the Spread of Sustainability Movement: Computational Analysis on Social Media Messages Promoting Climate Actions

被引:2
|
作者
Shin, Sumin [1 ]
Jiang, Ziyou [2 ]
Lim, Rachel Esther [1 ]
Lyu, Jewon [2 ]
机构
[1] Oklahoma State Univ, Sch Media & Strateg Commun, 315 Paul Miller, Stillwater, OK 74078 USA
[2] Univ Georgia, Dept Text Merchandising & Interiors, Athens, GA USA
关键词
BRANDED CONTENT; INFORMATION; ENGAGEMENT; BEHAVIOR; QUALITY; MODEL; EMOJI; COMMUNICATION; RICHNESS; HELP;
D O I
10.1080/10641734.2024.2366173
中图分类号
F [经济];
学科分类号
02 ;
摘要
Growing concerns about climate change have led to sustainability campaigns via social media. Few researchers have explored how public responses are influenced by social media messages about sustainability and what factors of these campaigns increase their success. This study examines how sustainability issues are communicated and what features of social media messages promote audience engagement by applying the information-quality and message-valence theories. This study used computational content analysis to collect and analyze tweets about a climate-action movement created by the United Nations for three years, from 2020 to 2022. Initially, 1,070,930 tweets were collected, and 59,181 tweets were retained to test the hypotheses. The results showed that the number of shares increased with high word count, the presence of hashtags, and visual content but decreased with URLs, a verified tag, and positive sentiment. Our findings extend the existing literature by elaborating the roles of information qualities in the context of social media messages about sustainability. This study provides communication practitioners with an equation model to predict shares of a climate-action campaign message on social media.
引用
收藏
页码:282 / 300
页数:19
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