This paper proposes a novel lexicon-based unsupervised sentimental analysis method to measure the $``\textit{hope}"$ and $``\textit{fear}"$ for the 2022 Ukrainian-Russian Conflict. $\textit{Reddit.com}$ is utilised as the main source of human reactions to daily events during nearly the first three months of the conflict. The top 50 $``hot"$ posts of six different subreddits about Ukraine and news (Ukraine, worldnews, Ukraina, UkrainianConflict, UkraineWarVideoReport, UkraineWarReports) and their relative comments are scraped and a data set is created. On this corpus, multiple analyses such as (1) public interest, (2) hope/fear score, (3) stock price interaction are employed. We promote using a dictionary approach, which scores the hopefulness of every submitted user post. The Latent Dirichlet Allocation (LDA) algorithm of topic modelling is also utilised to understand the main issues raised by users and what are the key talking points. Experimental analysis shows that the hope strongly decreases after the symbolic and strategic losses of Azovstal (Mariupol) and Severodonetsk. Spikes in hope/fear, both positives and negatives, are present after important battles, but also some non-military events, such as Eurovision and football games.

该论文提出了一种新的基于字典的无监督情感分析方法，用于衡量2022年乌克兰俄罗斯冲突中的“希望”和“恐惧”，并使用Reddit搭建数据集进行多项分析，利用主题模型算法LDA来理解用户提出的主要问题和要点。实验结果表明，随着Azovstal（Mariupol）和Severodonetsk的象征性和战略性损失，希望强烈下降。此外，重要战斗和一些非军事事件（如欧洲歌唱比赛和足球比赛）均存在希望/恐惧的大幅波动。

2022年俄乌冲突期间从Reddit帖子中测量希望和恐惧的情感分析