Data · dataset · 2017
Dataset: input and results related to the paper 'Anticipointment detection in event tweets'
Listed in DANS Data Station Social Sciences and Humanities and ODISSEI Portal — shown once because both records carry DOI 10.17026/dans-xcp-x989
Description
This dataset features the training models, emotion classifications and emotion patterns before and after events, related to the paper: F. Kunneman, M. van Mulken and A. Van den Bosch, Anticipointment detection in event tweets (under review) Abstract of the study: We developed a system to detect positive expectation, disappointment, and satisfaction in tweets that refer to events automatically discovered in the Twitter stream.
The emotional content shared on Twitter when referring to public events can provide insights into the presumed and experienced quality of the event. We expected to find a connection between positive expectation and disappointment, a succession that is sometimes referred to as anticipointment. The application of computational approaches makes it possible to detect the presence and strength of this hypothetical relation for a large number of events.
Read the rest (3 more)
We extracted events from a longitudinal data set of Dutch Twitter posts, and modeled classifiers to recognize emotion in the tweets related to those events by means of hashtag-labeled training data. After classifying all tweets before and after the events in our data set, we summarized the collective emotions by calculating the percentage of tweets classified with an emotion as well as ranking tweets based on the classifier confidence score for an emotion and selecting the 90th percentile.
Only a weak correlation of around 0.2 was found between positive expectation and disappointment, while a higher correlation of 0.6 was found between positive expectation and satisfaction. The most anticipointing events were events with a clear loss, such as a canceled event or when the favored sports team had lost. We conclude that senders of Twitter posts might be more inclined to share satisfaction than disappointment after a much anticipated event.
Subject period: January 1st 2011 until October 31st 2015 Date: start=2015-11-01; end=2016-02-28 (data collection)
Links
Where it is published
- Dataverse dataset page ssh.datastations.nl/dataset.xhtml?persistentId=doi%3A10.17026%2FDANS-XCP-X989 ↗
landing page · from ssh datastations nl
- Dataverse dataset page portal.odissei.nl/dataset.xhtml?persistentId=doi%3A10.17026%2FDANS-XCP-X989 ↗
landing page · from portal odissei nl
- DOI doi.org/10.17026/dans-xcp-x989 ↗
DOI / persistent id · from ssh datastations nl
Catalogue records · 2
- Dataverse API ssh.datastations.nl/api/datasets/:persistentId/?persistentId=doi%3A10.17026%2FDANS… ↗
metadata API · from ssh datastations nl
- Dataverse API portal.odissei.nl/api/datasets/:persistentId/?persistentId=doi%3A10.17026%2FDANS… ↗
metadata API · from portal odissei nl
Topics
- Stated by source
- Arts and Humanities · Arts and Humanities · Computer and Information Science · Computer and Information Science · Social Sciences · Social Sciences
- From keywords
- Computer Science & AI · Computer Science & AI · Humanities · Humanities · Machine learning · Machine learning · Natural language processing · Natural language processing · Social Science · Social Science
- Inferred from text
- Longitudinal study 65%
Provenance · 2 source records, 23 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DANS Data Station Social Sciences and Humanities | doi:10.17026/DANS-XCP-X989 | 11 d ago | JSON v1 |
| ODISSEI Portal | doi:10.17026/DANS-XCP-X989 | 8 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:460208 | mapping · portal odissei nl | vocabulary-mapper@1.0.0 | keywords['Natural Language Processing'] |
| concepts[field].anzsrc:field:460208 | mapping · ssh datastations nl | vocabulary-mapper@1.0.0 | keywords['Natural Language Processing'] |
| concepts[field].anzsrc:group:4611 | mapping · ssh datastations nl | vocabulary-mapper@1.0.0 | keywords['Machine learning'] |
| concepts[field].anzsrc:group:4611 | mapping · portal odissei nl | vocabulary-mapper@1.0.0 | keywords['Machine learning'] |
| concepts[field].dataverse_subject:arts-and-humanities | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:arts-and-humanities | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:computer-and-information-science | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:computer-and-information-science | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].dataverse_subject:social-sciences | source · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · portal odissei nl | connector:portal_odissei_nl@1.0.0 | /subjects |
| concepts[method].local:method:longitudinal-study | enrichment · ssh datastations nl | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| description | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /description |
| publication_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| title | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /name |
| updated_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| version_label | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 |