Impact and dynamics of hate and counter speech online

被引:15
|
作者
Garland, Joshua [1 ]
Ghazi-Zahedi, Keyan [2 ]
Young, Jean-Gabriel [3 ,4 ]
Hebert-Dufresne, Laurent [3 ,4 ]
Galesic, Mirta [1 ,4 ,5 ]
机构
[1] Santa Fe Inst, 1399 Hyde Pk Rd, Santa Fe, NM 87501 USA
[2] Max Planck Inst Math Sci, Inselstr 22, D-04103 Leipzig, Germany
[3] Univ Vermont, Dept Comp Sci, Burlington, VT 05405 USA
[4] Univ Vermont, Vermont Complex Syst Ctr, Burlington, VT 05405 USA
[5] Complex Sci Hub Vienna, Josefstadter Str 39, A-1080 Vienna, Austria
基金
美国国家科学基金会;
关键词
Hate speech; Counter speech; Twitter; Natural language processing; Time-series analysis; DETERMINANTS; BYSTANDERS; CYBERHATE; BEHAVIOR; VOICES;
D O I
10.1140/epjds/s13688-021-00314-6
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Citizen-generated counter speech is a promising way to fight hate speech and promote peaceful, non-polarized discourse. However, there is a lack of large-scale longitudinal studies of its effectiveness for reducing hate speech. To this end, we perform an exploratory analysis of the effectiveness of counter speech using several different macro- and micro-level measures to analyze 180,000 political conversations that took place on German Twitter over four years. We report on the dynamic interactions of hate and counter speech over time and provide insights into whether, as in 'classic' bullying situations, organized efforts are more effective than independent individuals in steering online discourse. Taken together, our results build a multifaceted picture of the dynamics of hate and counter speech online. While we make no causal claims due to the complexity of discourse dynamics, our findings suggest that organized hate speech is associated with changes in public discourse and that counter speech-especially when organized-may help curb hateful rhetoric in online discourse.
引用
收藏
页数:24
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