Comparing Emotional Valence Scores of Twitter Posts from Manual Coding and Machine Learning Algorithms to Gain Insights to Refine Interventions for Family Caregivers of Persons with Dementia.
Comparing Emotional Valence Scores of Twitter Posts from Manual Coding and Machine Learning Algorithms to Gain Insights to Refine Interventions for Family Caregivers of Persons with Dementia.
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DOI：
10.3233/shti220710
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发表时间：
2022-06-29
影响因子：
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通讯作者：
Lee, Haeyoung
中科院分区：
文献类型：
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作者：
Yoon, Sunmoo;Broadwell, Peter;Sun, Frederick F;Jang, Sun Joo;Lee, Haeyoung
我们随机抽取了2020年11月28日至12月9日期间提及痴呆/阿尔茨海默病的韩语推文（n= 12，413）。我们独立地应用了三种机器学习算法（Afinn，Syuzhet和Bing），使用自然语言处理（NLP）技术和定性手动评分来为推文分配情感效价分数。然后，我们比较了四个情绪效价分数的平均值和分布。对生成的图进行目视检查表明，每种方法均表现出独特的模式。NLP方法的总体平均情绪效价得分大多是中性的，而手动编码的得分略低（Afinn 0.029，95% CI [−0.019，0.077]; Syuzhet 0.266，[0.236，0.295]; Bing −0.271，[−0.289，−0.252];手动编码−1.601，[−1.632，−1.569]）。单因素方差分析（ANOVA）显示，归一化后的四个平均值之间无统计学显著差异。这些研究结果表明，NLP的应用可以相当有效地从韩语Twitter内容中提取情感效价分数，以获得有关痴呆症患者家庭幸福的见解。
We randomly extracted Korean-language Tweets mentioning dementia/Alzheimer’s disease (n= 12,413) from November 28 to December 9, 2020. We independently applied three machine learning algorithms (Afinn, Syuzhet, and Bing) using natural language processing (NLP) techniques and qualitative manual scoring to assign emotional valence scores to Tweets. We then compared the means and distributions of the four emotional valence scores. Visual examination of the graphs produced indicated that each method exhibited unique patterns. The aggregated mean emotional valence scores from the NLP methods were mostly neutral, vs. slightly negative for manual coding (Afinn 0.029, 95% CI [−0.019, 0.077]; Syuzhet 0.266, [0.236, 0.295]; Bing −0.271, [−0.289, −0.252]; manual coding −1.601, [−1.632, −1.569]). One-way analysis of variance (ANOVA) showed no statistically significant differences among the four means after normalization. These findings suggest that the application of NLP can be fairly effective in extracting emotional valence scores from Korean-language Twitter content to gain insights regarding family caregiving for a person with dementia.