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

Abstract

Abstract. 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 a cost-efficient way. This paper reviews a wide range of opinion mining methods, which have been developed for analyzing commercial product opinions and reviews posted on the Web, as to the capabilities they can offer for meeting the above challenges. The review has revealed the great potential of these methods for the analysis of textual citizens' contributions in public policy debates, both for assessing contributors' general attitudes-sentiments (positive, negative or neutral) towards the policy/decision under discussion, and also for extracting the main issues they raise (e.g. negative and positive aspects and effects, implementation barriers, improvement suggestions) and the corresponding attitudes-sentiments. Based on the conclusions of this review a basic framework for the use of opinion mining methods in eParticipation has been formulated.

Active and Passive Crowdsourcing in Government

“…blog postings, comments, opinions, etc. ), processing them using opinion mining techniques (Maragoudakis et al 2011). In particular, it performs the following three types of tasks:…”

“…), so it can be used for the calculation of various analytics. However, a large part of this content is in textual form, so opinion mining, defined as the advanced processing of text in order to extract sentiments, feelings, opinions and emotions (for a review of them see Maragoudakis et al 2011), will be a critical technology for processing it and maximizing knowledge extraction from it. The development and use of opinion mining first started in the private sector, as firms wanted to analyze comments and reviews about their products, which had been entered by their customers in various websites, in order to draw conclusions as to whether customers like the specific products or not (through sentiment analysis techniques), the particular features of the products that have been commented (through issues extraction techniques) and the orientations (positive, negative or neutral) of these comments (through sentiment analysis techniques).…”

Towards a global participatory platform

“…-Advanced processing tools for extracting knowledge and citizen opinion from typically unstructured, informal inputs. The application of text mining tools, topic-dependent sentiment analysis algorithms and issues extraction mechanisms promise that they can deliver important knowledge towards the further modelling and simulation of complex societal problems [42]. -Further exploration of collaborative governance methods and practices, giving the opportunity to citizens to participate in societal problem-solving and public service co-design, adhering to the Digital Agenda 2020 relevant provisions 18 .…”

Online Communities Support Policy-Making: The Need for Data Analysis

“…Teufl et al proposed a clustering and graphbased framework [20] to limit the need for manual analysis. Maragoudakis et al [10] reviewed different opinion mining methods and developed a framework to use them. The impact of social media to elections (especially in the Netherlands) is proven by [4].…”