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Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management

McDonald, G., Deveaud, R., Mccreadie, R. , Macdonald, C. and Ounis, I. (2015) Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management. In: 9th International AAAI Conference on Web and Social Media, Oxford, UK, 26-29 May 2015, pp. 654-657.

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Publisher's URL: http://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/view/10594

Abstract

Online Reputation Management (ORM) is concerned with the monitoring of public opinions on social media for entities such as commercial organisations. In particular, we investigate the task of reputation dimension classification, which aims to classify tweets that mention a business entity into different dimensions (e.g. "financial performance'' or "products and services''). However, producing a general reputation dimension classification system that can be used across businesses of different types is challenging, due to the brief nature of tweets and the lack of terms in tweets that relate to specific reputation dimensions. To tackle these issues, we propose a robust and effective tweet enrichment approach that expands tweets with additional discriminative terms from a contemporary Web corpus. Using the RepLab 2014 test collection, we show that our tweet enrichment approach outperforms effective baselines including the top performing submission to RepLab 2014. Moreover, we show that the achieved accuracy scores are very close to the upper bound that our approach could achieve on this collection.

Item Type:	Conference Proceedings
Keywords:	Online Reputation Management; Text Classification; Query expansion; Collection Enrichment
Status:	Published
Refereed:	Yes
Glasgow Author(s) Enlighten ID:	Mccreadie, Dr Richard and Macdonald, Professor Craig and Deveaud, Mr Romain and Ounis, Professor Iadh
Authors:	McDonald, G., Deveaud, R., Mccreadie, R., Macdonald, C., and Ounis, I.
College/School:	College of Science and Engineering > School of Computing Science
Copyright Holders:	Copyright © 2015 Association for the Advancement of Artificial Intelligence
Publisher Policy:	Reproduced in accordance with the copyright policy of the publisher
Related URLs:	Organisation

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References

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Deposit and Record Details

ID Code:	114997
Depositing User:	Dr Richard Mccreadie
Datestamp:	26 Jan 2016 11:09
Last Modified:	07 Nov 2022 13:27
Date of acceptance:	9 March 2015
Date of first online publication:	2015
Date Deposited:	18 January 2016
Data Availability Statement:	No