# Sentiment Analysis for Measuring Hope and Fear from Reddit Posts During the 2022 Russo-Ukrainian Conflict

arXiv: https://arxiv.org/abs/2301.08347 · HTML: https://mlsanity.com/paper/2301.08347/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 66 references that are in the map.
- First posted on arXiv 19 Jan 2023.

## Builds on (most cited first, 4 of 4)

- [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013)
- [Sentiment Analysis of Twitter Data for Predicting Stock Market Movements](https://mlsanity.com/paper/1610.09225/) (2016)
- [Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence](https://mlsanity.com/paper/2108.13293/) (2021)
- [A review of sentiment computation methods with R packages](https://mlsanity.com/paper/1901.08319/) (2019)

## Built on by (most cited first, 1 of 1)

- [Quantifying Extreme Opinions on Reddit Amidst the 2023 Israeli-Palestinian Conflict](https://mlsanity.com/paper/2412.10913/) (2024)

## Abstract (arXiv)

This paper proposes a novel lexicon-based unsupervised sentimental analysis method to measure the ``textithope" and ``textitfear" for the 2022 Ukrainian-Russian Conflict. textitReddit.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.