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ASEM: Mining Aspects and Sentiment of Events from Microblog

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Kai LeiAuthors Info & Claims

CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

Pages 1923 - 1926

https://doi.org/10.1145/2806416.2806622

Published: 17 October 2015 Publication History

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Abstract

Microblogs contain the most up-to-date and abundant opinion information on current events. Aspect-based opinion mining is a good way to get a comprehensive summarization of events. The most popular aspect based opinion mining models are used in the field of product and service. However, existing models are not suitable for event mining. In this paper we propose a novel probabilistic generative model (ASEM) to simultaneously discover aspects and the specified opinions. ASEM incorporate a sequence labeling model(CRF) into a generative topic model. Additionally, we adopt a set of features for separating aspects and sentiments. Moreover, we novelly present a continuously learning model. It can utilize the knowledge of one event to learn another, and get a better performance. We use five real world events to do experiment. The experimental results show that ASEM extracts aspects and sentiments well, and ASEM outperforms other state-of-art models and the intuitive two-step method.

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Cited By

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Guo YWang TChen WKaptchuk TLi XGao XYao JTang XXu Z(2022)Acceptability of Traditional Chinese Medicine in Chinese People Based on 10-Year's Real World Study With Mutiple Big Data MiningFrontiers in Public Health10.3389/fpubh.2021.8117309Online publication date: 11-Jan-2022
https://doi.org/10.3389/fpubh.2021.811730
Ullah AKhan SNawi N(2022)Review on sentiment analysis for text classification techniques from 2010 to 2021Multimedia Tools and Applications10.1007/s11042-022-14112-382:6(8137-8193)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11042-022-14112-3
Alattar FShaalan K(2021)A Survey on Opinion Reason Mining and Interpreting Sentiment VariationsIEEE Access10.1109/ACCESS.2021.30639219(39636-39655)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3063921
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Index Terms

ASEM: Mining Aspects and Sentiment of Events from Microblog
1. Information systems
  1. Information retrieval

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Published In

CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

October 2015

1998 pages

ISBN:9781450337946

DOI:10.1145/2806416

General Chairs:
James Bailey
The University of Melbourne
,
Alistair Moffat
The University of Melbourne
,
Program Chairs:
Charu C. Aggarwal
IBM
,
Maarten de Rijke
University of Amsterdam
,
Ravi Kumar
Google
,
Vanessa Murdock
Microsoft
,
Timos Sellis
RMIT University
,
Jeffrey Xu Yu
Chinese University of Hong Kong

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2015

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Short-paper

Funding Sources

Specialized Research Fund for the Doctoral Program of Higher Education
Natural Science Foundation of China
Ministry of Education & China Mobile Joint Research Fund Program

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CIKM'15

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CIKM'15: 24th ACM International Conference on Information and Knowledge Management

October 18 - 23, 2015

Melbourne, Australia

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CIKM '15 Paper Acceptance Rate 165 of 646 submissions, 26%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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CIKM '25

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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

View all

Guo YWang TChen WKaptchuk TLi XGao XYao JTang XXu Z(2022)Acceptability of Traditional Chinese Medicine in Chinese People Based on 10-Year's Real World Study With Mutiple Big Data MiningFrontiers in Public Health10.3389/fpubh.2021.8117309Online publication date: 11-Jan-2022
https://doi.org/10.3389/fpubh.2021.811730
Ullah AKhan SNawi N(2022)Review on sentiment analysis for text classification techniques from 2010 to 2021Multimedia Tools and Applications10.1007/s11042-022-14112-382:6(8137-8193)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11042-022-14112-3
Alattar FShaalan K(2021)A Survey on Opinion Reason Mining and Interpreting Sentiment VariationsIEEE Access10.1109/ACCESS.2021.30639219(39636-39655)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3063921
Maitama JIdris NZakari A(2020)A Systematic Mapping Study of the Empirical Explicit Aspect Extractions in Sentiment AnalysisIEEE Access10.1109/ACCESS.2020.30036258(113878-113899)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3003625
Corallo ATrono AFortunato LPettinato FSchina L(2019)Cultural Event Management and Urban E-Planning Through Bottom-Up User ParticipationSmart Cities and Smart Spaces10.4018/978-1-5225-7030-1.ch046(1011-1030)Online publication date: 2019
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Corallo ATrono AFortunato LPettinato FSchina L(2018)Cultural Event Management and Urban e-Planning Through Bottom-Up User ParticipationInternational Journal of E-Planning Research10.4018/IJEPR.20180101027:1(15-33)Online publication date: 1-Jan-2018
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Corallo ATrono AFortunato LPettinato FSchina L(2018)Cultural Event Management and Urban E-Planning Through Bottom-Up User ParticipationE-Planning and Collaboration10.4018/978-1-5225-5646-6.ch050(1059-1078)Online publication date: 2018
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Atreja SAggarwal PMohapatra PDumrewal ABasu ADasgupta GBerkovsky SHijikata YRekimoto JBurnett MBillinghurst MQuigley A(2018)CiticafeProceedings of the 23rd International Conference on Intelligent User Interfaces10.1145/3172944.3172955(617-628)Online publication date: 5-Mar-2018
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Zuo YWu JZhang HWang DXu K(2018)Complementary Aspect-Based Opinion MiningIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.276408430:2(249-262)Online publication date: 1-Feb-2018
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