Solidarity and strife after the Atlanta spa shootings: A mixed methods study characterizing Twitter discussions by qualitative analysis and machine learning.
Solidarity and strife after the Atlanta spa shootings: A mixed methods study characterizing Twitter discussions by qualitative analysis and machine learning.
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DOI：
10.3389/fpubh.2023.952069
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发表时间：
2023
影响因子：
5.2
通讯作者：
Kennedy, Chris J.
中科院分区：
文献类型：
--
作者：
Criss, Shaniece;Nguyen, Thu T.;Michaels, Eli K.;Gee, Gilbert C.;Kiang, Mathew V.;Nguyen, Quynh C.;Norton, Samantha;Titherington, Eli;Nguyen, Leah;Yardi, Isha;Kim, Melanie;Thai, Nhung;Shepherd, Ariel;Kennedy, Chris J.
2021年3月16日，一名白人男子在亚特兰大地区的水疗和按摩院开枪打死8人，其中6人是亚洲女性。本研究的目的是：(1)定性地总结亚特兰大水疗中心枪击事件后与种族、民族和种族主义相关的推文主题，(2)使用仇恨言论分析的新方法检查亚特兰大水疗中心枪击事件前后仇恨言论表达和团结的时间趋势。从2021年1月到4月，随机收集了1%的公开推文样本。分析样本包括708,933条使用种族相关关键词的推文。该样本使用一种新开发的方法来分析仇恨言论，该方法将面项反应理论与深度学习相结合，以测量仇恨言论的连续体，从团结种族相关的言论到使用暴力，种族主义语言。本文随机抽取2021年1月至3月15日亚特兰大温泉枪击案发生前的1000条提到亚洲人的推文和3月17日至28日枪击案发生后的2000条提到亚洲人的推文进行定性内容分析，捕捉枪击案发生后的即时反应和讨论。出现的定性主题包括团结（枪击前4%，枪击后17%）、谴责枪击（枪击后9%）、种族主义（枪击前10%，枪击后18%）、种族主义语言在大流行期间的作用（2%，枪击后6%）、交叉脆弱性（4%，枪击后6%）、亚裔和黑人反对种族主义斗争之间的关系（5%，枪击后7%），以及不相关的讨论（74%，枪击后37%）。量化仇恨言论模型显示，提及亚洲人表达种族主义的推文比例有所下降（从事件发生前7天的1.4%降至事件发生后3天的1.0%）。提及亚洲人表达团结言论的推文比例增加了20%（同期从22.7%增加到27.2%）（p < 0.001），并在大约2周内恢复到之前的比例。我们的分析强调了歧视的一些复杂性，以及对网络言论进行细致评估的重要性。调查结果表明，追踪仇恨和团结言论的重要性。通过了解社交媒体上出现的对话，我们可以了解产生团结促进信息和抑制仇恨信息的可能方法。
On March 16, 2021, a white man shot and killed eight victims, six of whom were Asian women at Atlanta-area spa and massage parlors. The aims of the study were to: (1) qualitatively summarize themes of tweets related to race, ethnicity, and racism immediately following the Atlanta spa shootings, and (2) examine temporal trends in expressions hate speech and solidarity before and after the Atlanta spa shootings using a new methodology for hate speech analysis. A random 1% sample of publicly available tweets was collected from January to April 2021. The analytic sample included 708,933 tweets using race-related keywords. This sample was analyzed for hate speech using a newly developed method for combining faceted item response theory with deep learning to measure a continuum of hate speech, from solidarity race-related speech to use of violent, racist language. A qualitative content analysis was conducted on random samples of 1,000 tweets referencing Asians before the Atlanta spa shootings from January to March 15, 2021 and 2,000 tweets referencing Asians after the shooting from March 17 to 28 to capture the immediate reactions and discussions following the shootings. Qualitative themes that emerged included solidarity (4% before the shootings vs. 17% after), condemnation of the shootings (9% after), racism (10% before vs. 18% after), role of racist language during the pandemic (2 vs. 6%), intersectional vulnerabilities (4 vs. 6%), relationship between Asian and Black struggles against racism (5 vs. 7%), and discussions not related (74 vs. 37%). The quantitative hate speech model showed a decrease in the proportion of tweets referencing Asians that expressed racism (from 1.4% 7 days prior to the event from to 1.0% in the 3 days after). The percent of tweets referencing Asians that expressed solidarity speech increased by 20% (from 22.7 to 27.2% during the same time period) (p < 0.001) and returned to its earlier rate within about 2 weeks. Our analysis highlights some complexities of discrimination and the importance of nuanced evaluation of online speech. Findings suggest the importance of tracking hate and solidarity speech. By understanding the conversations emerging from social media, we may learn about possible ways to produce solidarity promoting messages and dampen hate messages.
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影响因子：
8
作者：
Dreyer, Benard P.;Trent, Maria;Stein, Fernando
通讯作者：
Stein, Fernando
DOI：
10.3390/ijerph17197032
发表时间：
2020-09-25
影响因子：
--
作者：
Nguyen TT;Criss S;Dwivedi P;Huang D;Keralis J;Hsu E;Phan L;Nguyen LH;Yardi I;Glymour MM;Allen AM;Chae DH;Gee GC;Nguyen QC
通讯作者：
Nguyen QC
影响因子：
0.6
作者：
Chaudhry, Irfan
通讯作者：
Chaudhry, Irfan
DOI：
10.3390/ijerph18115693
发表时间：
2021-05-26
影响因子：
--
作者：
Criss S;Nguyen TT;Norton S;Virani I;Titherington E;Tillmanns EL;Kinnane C;Maiolo G;Kirby AB;Gee GC
通讯作者：
Gee GC
DOI：
10.3390/ijerph16101766
发表时间：
2019-05-02
影响因子：
--
作者：
Nguyen, Thu T.;Criss, Shaniece;Nguyen, Quynh C.
通讯作者：
Nguyen, Quynh C.