Social media empowers citizens to raise the voice and expressed civil outrage leads to collective action to change the society. Since social media welcomes anyone regardless of the political ideology or perspectives, social media is where the supporters and opponents of specific issue discuss. This study attempts to empirically examine a recent anti-racism movement initiated by the death of George Floyd with the lens of stance prediction and aspect-based sentiment analysis (ABSA). First, this study found the stance of the tweet and users do change over the course of the protest. Furthermore, there are more users who shifted the stance compared to those who maintained the stance. Second, both supporters and opponents expressed negative sentiment more on nine extracted aspects. This indicates that there was no significant difference of sentiment among supporters and opponents and raise a caution in predicting stance based on the sentiment. The contribution of the study is two-fold. First, ABSA was explored in the context of computational social science and second, stance prediction was first attempted at scale.
翻译:社会媒体赋予公民提高声音和表达公民愤怒的权力,从而导致采取集体行动来改变社会。由于社会媒体欢迎任何人,而不论其政治意识形态或观点如何,社会媒体就是具体问题的支持者和反对者讨论的地方。本研究报告试图用立场预测和基于方方面面的情绪分析(ABSA)的视角,对乔治·弗洛伊德死后最近发起的反种族主义运动进行实证性审查。首先,本研究报告发现推特的姿态,用户在抗议过程中确实有所改变。此外,与保持立场的用户相比,有更多的用户改变了立场。第二,支持者和反对者对9个抽取的方面表达了更多的负面情绪。这表明支持者和反对者之间没有重大情绪差异,并提醒人们要根据这种情绪预测立场。研究的贡献有两重。首先,在计算社会科学方面对ABSA进行了探讨,第二,首次尝试了立场预测。