ArticleData in brief2025
ID-SMSA: Indonesian stock market dataset for sentiment analysis.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- ID-SMSA: Indonesian stock market dataset for sentiment analysis.Data in brief · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social media has impacted daily life, affecting people's habits regarding accessing and sharing information. Among the platforms, X (formerly Twitter) gives users the freedom of speech to express their subjects and topics. Hence, users express their opinions on every topic, from light-hearted to heavy topics such as politics and the economy. This vast opinion from users creates a valuable resource for research. This paper presents the Indonesian Stock Market Dataset for Sentiment Analysis (ID-SMSA), a collection of 3288 tweets discussing the top 10 largest market caps in the Indonesian stock market as of March 2023. The dataset is in Indonesian and an English translated version is provided, making it the first Indonesian-language dataset discussing the Indonesian stock market. Human annotators labelled each tweet as positive, neutral, or negative based on baseline annotation characteristics criteria created and reviewed by an expert in clinical psychology. A voting system determines which tweets to include in the dataset. This creates a consistent dataset that reflects clear and agreed-upon sentiments and removes ambiguous and contradictory data. The voted tweets include 2339 positive, 999 neutral, and 1025 negative sentiments. This dataset supports research into Indonesian stock market growth and the role of social media in financial discussions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.