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Sentiment popularity - Amazon Mechanical Turk dataset

Sentiment popularity - Amazon Mechanical Turk dataset
Sentiment popularity - Amazon Mechanical Turk dataset
Dataset re-collected from an original dataset collected by Pang, B., and Lee, L. 2004. "A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts". In Proceedings of the 42nd annual meeting on Association for Computational Linguistics. The dataset presents a binary classification problem, with workers asked to select either positive (1) or negative (0) for a 500 sentences extracted from movie reviews, with gold labels assigned by the website. It contains 10,000 sentiment judgements collected from 143 using the Amazon Mechanical Turk platform. Each row is in the format WorkerID, TaskID, Worker label, Gold label, time spent on the judgement by the worker
University of Southampton
VENANZI, MATTEO
6c1596de-424e-48ef-8248-09c64a05a9fa
Teacy, William
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Rogers, Alexander
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas
ab3d94cc-247c-4545-9d1e-65873d6cdb30
VENANZI, MATTEO
6c1596de-424e-48ef-8248-09c64a05a9fa
Teacy, William
5f962a10-9ab5-4b19-8016-cc72588bdc6a
Rogers, Alexander
f9130bc6-da32-474e-9fab-6c6cb8077fdc
Jennings, Nicholas
ab3d94cc-247c-4545-9d1e-65873d6cdb30

VENANZI, MATTEO, Teacy, William, Rogers, Alexander and Jennings, Nicholas (2015) Sentiment popularity - Amazon Mechanical Turk dataset. University of Southampton [Dataset]

Record type: Dataset

Abstract

Dataset re-collected from an original dataset collected by Pang, B., and Lee, L. 2004. "A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts". In Proceedings of the 42nd annual meeting on Association for Computational Linguistics. The dataset presents a binary classification problem, with workers asked to select either positive (1) or negative (0) for a 500 sentences extracted from movie reviews, with gold labels assigned by the website. It contains 10,000 sentiment judgements collected from 143 using the Amazon Mechanical Turk platform. Each row is in the format WorkerID, TaskID, Worker label, Gold label, time spent on the judgement by the worker

Other
SP_amt.csv - Dataset
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More information

Published date: 2015
Additional Information: Supports: Venanzi, Matteo, Teacy, W.T.L., Rogers, Alex and Jennings, Nicholas R. (2015) Bayesian modelling of community-based multidimensional trust in participatory sensing under data sparsity. In, International Joint Conference on Artificial Intelligence (IJCAI-15), Buenos Aires, AR, 25 - 31 Jul 2015. 8pp, 717-724.
Organisations: Electronics & Computer Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 376544
URI: https://eprints.soton.ac.uk/id/eprint/376544
PURE UUID: 08ae378d-c839-4d09-8c0c-f09c42210a82

Catalogue record

Date deposited: 24 Apr 2015 17:01
Last modified: 10 Nov 2017 05:27

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Contributors

Creator: MATTEO VENANZI
Creator: William Teacy
Creator: Alexander Rogers
Creator: Nicholas Jennings

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