針對亞裔的仇恨犯罪已經成為需要關注的議題，尤其是COVID-19疫情期間。本文旨在通過利用Economic Job Market Rumors論壇的文字資料和採用計量經濟學模型，了解在網絡平台上對亞洲人形象。通過Word2Vec，我們發現不同的民族和國籍所討論的主題和所使用的詞彙是不同的。此外，這些討論中根據主題會使用特定詞彙，例如，在與中國有關的主題時，會出現與貿易有關的字詞，這反映了中美貿易戰的影響。此外，透過使用雙重選擇(double selection)，觀察與個人特徵相關的詞彙與亞裔主題的相關性以及信賴區間。
本文發現根據不同的前處理會影響研究結果。並且發現在正向字詞及負向字詞皆有顯著，這顯示了此論壇針對亞裔族群的雙面印象。

Hate crimes targeting individuals of Asian descent have emerged as a significant concern, particularly in light of the ongoing COVID-19 pandemic. This research aims to contribute to the understanding of how Asians are portrayed in online platforms by utilizing textual data from the Economic Job Market Rumors forum and employing econometric models. Through extensive analysis, it has been observed that the subjects discussed and the vocabulary employed vary across different ethnic groups and nationalities. Moreover, specific terms used in these threads directly correspond to real-world events. For instance, when examining conversations related to China, there is a notable presence of trade-related terminology, which reflects the influence of the trade war era. Furthermore, by employing the double selection method and determining the significance of words associated with individual characteristics, along with the inclusion of confidence intervals, the study sheds light on the variations and similarities that arise based on the chosen preprocessing techniques. And not only negative but also positive terms are significant, underscoring a polarized impression prevalent within the forum's community on Asians.

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