Data · dataset · 2023
Sentiment analysis dataset
Listed in ScienceDB
Description
This dataset uses Sina Weibo as the data source for user sentiment analysis of online public opinion events, and captures the emotional content posted by netizens related to the "Australian wildfire" incident, "Notre Dame Cathedral fire" incident, "Henan exceptionally heavy rain" incident, "Turkey earthquake" incident, "Yinchuan barbecue restaurant explosion" incident, and "China Eastern Airlines MU5735" several representative public security public opinion events as keywords. and store the image content contained in the post in a .jpg format.
After scraping, a total of 3796 pictures were obtained, and the pictures that were not related to the event or duplicate pictures were denoised, and finally 2831 pictures were obtained.Two graduate students were convened to carry out two-person annotation, using Plutchik "Emotion Wheel" as a reference for annotation, and combining the text corresponding to the picture to label the emotion category of the picture.
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When there is an inconsistency in the labeling, this paper convenes the annotation group for full discussion, and when the annotation opinions are still not unagreed, the expert opinion is introduced and the final emotional label is determined. The emotional categories marked in this paper were positive, negative, and neutral, with the number of positives being 974, neutral being 552, and being negative being 1305.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.12641 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.12641 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:text | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |