Attention-Seeking Strategies: An Investigation of Sexual Assault Organizations' Communication Tactics on Twitter

被引：0

作者：

Xue, Jia ^{[1
,2
,3
]}

Shi, Hong ^{[1
]}

Zhang, Qiaoru ^{[1
]}

Fan, Jingchuan ^{[1
]}

Shier, Micheal ^{[1
]}

机构：

[1] Univ Toronto, Toronto, ON, Canada

[2] Univ Toronto, Factor Inwentash Fac Social Work, 246 Bloor St West, Toronto, ON M5S 1V4, Canada

[3] Univ Toronto, Fac Informat, 246 Bloor St West, Toronto, ON M5S 1V4, Canada

来源：

NONPROFIT AND VOLUNTARY SECTOR QUARTERLY | 2025年 / 54卷 / 02期

关键词：

attention-seeking strategy; Twitter; machine learning; ordinary least squares; Canada; ENGAGEMENT; NONPROFITS; BRAND; TOOL;

D O I：

10.1177/08997640241247025

中图分类号：

D58 [社会生活与社会问题]; C913 [社会生活与社会问题];

学科分类号：

摘要：

This study examines the attention-seeking strategies of sexual assault organizations on Twitter in Canada, exploring the factors influencing the level of attention received. Drawing on the foundation work of Guo and Saxon's four-factor explanatory model, the research extends and refines the model by incorporating new factors, including Covid-related content, network size, intended audience, direct services, donations, and visual content. The study's methodology involved sampling 124 sexual assault and rape crisis centers in Canada, collecting Twitter data (n = 320,836 Tweets up to April 2023), and employing ordinary least squares and fixed effect regression analysis. Results showed significant relationships between these factors and attention received, providing insights for both theoretical understanding and practical guidance.

引用

页码：378 / 410

页数：33