A Review of Opinion Mining Methods for Analyzing Citizens' Contributions in Public Policy Debate

@inproceedings{Maragoudakis2011ARO,
  title={A Review of Opinion Mining Methods for Analyzing Citizens' Contributions in Public Policy Debate},
  author={Manolis Maragoudakis and Euripidis Loukis and Yannis Charalabidis},
  booktitle={ePart},
  year={2011}
}
Electronic Participation (eParticipation), both in its traditional form and in its emerging Web 2.0 based form, results in the production of large quantities of textual contributions of citizens concerning government policies and decisions under formation, which contain valuable relevant opinions and knowledge of the society, however are exploited to a limited only extent. It is of critical importance to analyze these contributions in order to extract the opinions and knowledge they contain in… 

Opinion Mining and Sentiment Analysis in Policy Formulation Initiatives: The EU-Community Approach

TLDR
A novel approach to OM and SA use is described as part of an advanced ICT-based method of exploiting political content created in the Internet, and especially in social media, by experts 'expertsourcing', aiming to leverage the extensive policy community of the European Union, which is developed in the European EU-Community project.

Web 2.0 in Governance: A Framework for Utilizing Social Media and Opinion Mining Methods and Tools in Policy Deliberation

TLDR
This chapter presents a novel policy analysis framework, proposing a Web-based platform that enables publishing content and micro-applications to multiple Web 2.0 social media and collecting citizens’ interactions with efficient use of Application Programming Interfaces (APIs) of these media.

Strategies for mining opinions: A survey

TLDR
The paper presents an extensive literature review and highlights the present methods available in the field of opinion mining and discusses a work flow to mine the opinions though a useful and efficient system.

Combining Technocrats’ Expertise with Public Opinion Through an Innovative e-Participation Platform

TLDR
Evaluation results show that users appreciate the potential of exploiting the synergy of machine and human reasoning enabled by the proposed platform through a combination of data mining and structured consultation/argumentation - collaborative decision-making services.

Mining opinion components from unstructured reviews: A review

Towards a Rationalisation of Social Media Exploitation in Government Policy-Making Processes

Fraunhofer FOKUS Institute There has been significant research and practice oriented towards the rational exploitation of the rapidly expanding social media by private sector enterprises. However,

Evaluating Citizen Comments in Public Consultations Using Data Mining: Evaluating Citizen Comments in Public Consultations Using Data Mining: Analyzing Legislation Comments for the Greek General Commercial Registry

In the present paper, in the context of a pilot application, comments that appear on the ConsultationWebsite of the Ministry of Development and Investments of Greece, concerning the draft provisions

Opinion Mining on Food Services using Topic Modeling and Machine Learning Algorithms

TLDR
The objective of this work is to analyze every review of the user and classify if it is positive, negative or neutral in nature, which is called opinion mining, using Machine Learning algorithms.

Participative Public Policy Making Through Multiple Social Media Platforms Utilization

Described is the research concerning the systematic, intensive and centralized web 2.0 social media exploitation by government agencies for widening and enhancing participative public policy making,

References

SHOWING 1-10 OF 70 REFERENCES

A holistic lexicon-based approach to opinion mining

TLDR
This paper proposes a holistic lexicon-based approach to solving the problem of determining the semantic orientations (positive, negative or neutral) of opinions expressed on product features in reviews by exploiting external evidences and linguistic conventions of natural language expressions.

Mining product reputations on the Web

TLDR
A new framework for mining product reputations on the Internet is presented, which offers a drastic reduction in the overall cost of reputation analysis over that of conventional survey approaches and supports the discovery of knowledge from the pool of opinions on the web.

SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining

TLDR
SENTIWORDNET is a lexical resource in which each WORDNET synset is associated to three numerical scores Obj, Pos and Neg, describing how objective, positive, and negative the terms contained in the synset are.

Determining Term Subjectivity and Term Orientation for Opinion Mining

TLDR
The task of deciding whether a given term has a positive connotations, or a negative connotation, or has no subjective connotation at all is confronted, and it is shown that determining subjectivity and orientation is a much harder problem than determining orientation alone.

Hidden sentiment association in chinese web opinion mining

TLDR
A novel mutual reinforcement approach to deal with the feature-level opinion mining problem, which can largely predict opinions relating to different product features, even for the case without the explicit appearance of product feature words in reviews.

Determining the semantic orientation of terms through gloss classification

TLDR
This paper presents a new method for determining the orientation of subjective terms based on the quantitative analysis of the glosses of such terms given in on-line dictionaries, and on the use of the resulting term representations for semi-supervised term classification.

ARSA: a sentiment-aware model for predicting sales performance using blogs

TLDR
ARSA is presented, an autoregressive sentiment-aware model, to utilize the sentiment information captured by S-PLSA for predicting product sales performance and is compared with alternative models that do not take into account the sentiment Information.

Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis

TLDR
A new approach to phrase-level sentiment analysis is presented that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions, achieving results that are significantly better than baseline.

Knowledge Transfer and Opinion Detection in the TREC 2006 Blog Track

The paper describes the opinion detection system developed in Carnegie Mellon University for TREC 2006 Blog track. The system performed a two-stage process: passage retrieval and opinion detection.

Opinion observer: analyzing and comparing opinions on the Web

TLDR
A novel framework for analyzing and comparing consumer opinions of competing products is proposed, and a new technique based on language pattern mining is proposed to extract product features from Pros and Cons in a particular type of reviews.
...