Identifying emotions in earthquake tweets

被引:1
|
作者
Anthony, Patricia [1 ]
Wong, Jennifer Hoi Ki [2 ]
Joyce, Zita [3 ]
机构
[1] Lincoln Univ, Fac Environm Soc & Design, Christchurch, New Zealand
[2] Univ Canterbury, Sch Psychol Speech & Hearing, Christchurch, New Zealand
[3] Univ Canterbury, Sch Language Social & Polit Sci, Christchurch, New Zealand
关键词
Emotion identification; Earthquake tweets; Machine learning; SOCIAL MEDIA; COMMUNITY; DISASTER; IMPACT; FACEBOOK;
D O I
10.1007/s00146-024-02044-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Christchurch, New Zealand experienced devastating earthquakes on September 4, 2010, and February 22, 2011, resulting in extensive infrastructural damage and leaving lasting psychological scars of fear, depression, shock, and anger among the local population. Even after thirteen years, the aftermath of these earthquakes continues to deeply affect these individuals, as they grapple with enduring emotional challenges. Social media, particularly X (formerly Twitter), has emerged as a prominent platform for individuals to express their emotions, and during earthquake occurrences, people turn to Twitter to share their feelings in real-time. This study focuses on examining the emotional patterns exhibited in "earthquake tweets" posted by individuals affected by the Christchurch earthquakes between 2010 and 2019. We utilise machine learning techniques to classify these tweets into six classes of emotions of anger, fear, grateful, humour, sympathy and worry. The analysis shows a progressive increase in the percentage of tweets expressing fear and worry over the years. This finding indicates that the community continues to experience a heightened sense of fear and worry whenever earthquakes occur.
引用
收藏
页数:18
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