ReUS: A Real-Time Unsupervised System For Monitoring Opinion Streams

Andi Rexha, Mauro Dragoni, Marco Federici

Research output: Contribution to journalArticle

Abstract

Background An actual challenge within the sentiment
analysis research area is the extraction of polarity values
associated with specic aspects (or opinion targets)
contained in user generated content. This task, called
aspect-based sentiment analysis bring new challenges
like the disambiguation of words' role within text and
the inference of correct polarity values based on the
domain in which a text occurs. The former requires
strategies able to understand how each word is used
in a specic context in order to annotate it as aspect
or not. The latter need to be addressed with unsupervised
solutions in order to make a system ecient for
real-time tasks and at the same time
exible in order to
adopt it in any domain without requiring the training
of sentiment models. Finally, the deployment of such
system into real-world scenarios needs the development
of usable solutions for accessing and analyzing data.
Methods This paper presents the ReUS platform: a system
integrating an unsupervised approach, based on
open information extraction strategies, for performing
real-time aspect-based sentiment analysis together with
facilities supporting decision makers in the analysis and
visualization of collected data.
Results The ReUS platform has been validated from a
quantitative and qualitative perspectives. First, the aspect
extraction and polarity inference capabilities have been evaluated on three dataset used in likewise editions
of SemEval. Second, a user group has been invited
to judge the usability of the platform.
Conclusion The developed platform demonstrated to be
suitable for being used into real-world scenarios requiring
(i) the capability of processing real-time opinionbased
documents streams and (ii) the availability of
usable facilities for analyzing and visualizing collected
data. Examples of possible analysis and visualizations
includes the presentation of lists ranking aspects by
their importance of by their polarity values computed
within the whole data repository. This kind of analysis
enables, for instance, the discovery of product issues.
LanguageEnglish
JournalCognitive Computing
StatusPublished - 2018

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ReUS: A Real-Time Unsupervised System For Monitoring Opinion Streams. / Rexha, Andi; Dragoni, Mauro; Federici, Marco.

In: Cognitive Computing, 2018.

Research output: Contribution to journalArticle

@article{e7f835077705405087add8146091b476,
title = "ReUS: A Real-Time Unsupervised System For Monitoring Opinion Streams",
abstract = "Background An actual challenge within the sentimentanalysis research area is the extraction of polarity valuesassociated with specic aspects (or opinion targets)contained in user generated content. This task, calledaspect-based sentiment analysis bring new challengeslike the disambiguation of words' role within text andthe inference of correct polarity values based on thedomain in which a text occurs. The former requiresstrategies able to understand how each word is usedin a specic context in order to annotate it as aspector not. The latter need to be addressed with unsupervisedsolutions in order to make a system ecient forreal-time tasks and at the same time exible in order toadopt it in any domain without requiring the trainingof sentiment models. Finally, the deployment of suchsystem into real-world scenarios needs the developmentof usable solutions for accessing and analyzing data.Methods This paper presents the ReUS platform: a systemintegrating an unsupervised approach, based onopen information extraction strategies, for performingreal-time aspect-based sentiment analysis together withfacilities supporting decision makers in the analysis andvisualization of collected data.Results The ReUS platform has been validated from aquantitative and qualitative perspectives. First, the aspectextraction and polarity inference capabilities have been evaluated on three dataset used in likewise editionsof SemEval. Second, a user group has been invitedto judge the usability of the platform.Conclusion The developed platform demonstrated to besuitable for being used into real-world scenarios requiring(i) the capability of processing real-time opinionbaseddocuments streams and (ii) the availability ofusable facilities for analyzing and visualizing collecteddata. Examples of possible analysis and visualizationsincludes the presentation of lists ranking aspects bytheir importance of by their polarity values computedwithin the whole data repository. This kind of analysisenables, for instance, the discovery of product issues.",
author = "Andi Rexha and Mauro Dragoni and Marco Federici",
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language = "English",
journal = "Cognitive Computing",
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AU - Dragoni,Mauro

AU - Federici,Marco

PY - 2018

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N2 - Background An actual challenge within the sentimentanalysis research area is the extraction of polarity valuesassociated with specic aspects (or opinion targets)contained in user generated content. This task, calledaspect-based sentiment analysis bring new challengeslike the disambiguation of words' role within text andthe inference of correct polarity values based on thedomain in which a text occurs. The former requiresstrategies able to understand how each word is usedin a specic context in order to annotate it as aspector not. The latter need to be addressed with unsupervisedsolutions in order to make a system ecient forreal-time tasks and at the same time exible in order toadopt it in any domain without requiring the trainingof sentiment models. Finally, the deployment of suchsystem into real-world scenarios needs the developmentof usable solutions for accessing and analyzing data.Methods This paper presents the ReUS platform: a systemintegrating an unsupervised approach, based onopen information extraction strategies, for performingreal-time aspect-based sentiment analysis together withfacilities supporting decision makers in the analysis andvisualization of collected data.Results The ReUS platform has been validated from aquantitative and qualitative perspectives. First, the aspectextraction and polarity inference capabilities have been evaluated on three dataset used in likewise editionsof SemEval. Second, a user group has been invitedto judge the usability of the platform.Conclusion The developed platform demonstrated to besuitable for being used into real-world scenarios requiring(i) the capability of processing real-time opinionbaseddocuments streams and (ii) the availability ofusable facilities for analyzing and visualizing collecteddata. Examples of possible analysis and visualizationsincludes the presentation of lists ranking aspects bytheir importance of by their polarity values computedwithin the whole data repository. This kind of analysisenables, for instance, the discovery of product issues.

AB - Background An actual challenge within the sentimentanalysis research area is the extraction of polarity valuesassociated with specic aspects (or opinion targets)contained in user generated content. This task, calledaspect-based sentiment analysis bring new challengeslike the disambiguation of words' role within text andthe inference of correct polarity values based on thedomain in which a text occurs. The former requiresstrategies able to understand how each word is usedin a specic context in order to annotate it as aspector not. The latter need to be addressed with unsupervisedsolutions in order to make a system ecient forreal-time tasks and at the same time exible in order toadopt it in any domain without requiring the trainingof sentiment models. Finally, the deployment of suchsystem into real-world scenarios needs the developmentof usable solutions for accessing and analyzing data.Methods This paper presents the ReUS platform: a systemintegrating an unsupervised approach, based onopen information extraction strategies, for performingreal-time aspect-based sentiment analysis together withfacilities supporting decision makers in the analysis andvisualization of collected data.Results The ReUS platform has been validated from aquantitative and qualitative perspectives. First, the aspectextraction and polarity inference capabilities have been evaluated on three dataset used in likewise editionsof SemEval. Second, a user group has been invitedto judge the usability of the platform.Conclusion The developed platform demonstrated to besuitable for being used into real-world scenarios requiring(i) the capability of processing real-time opinionbaseddocuments streams and (ii) the availability ofusable facilities for analyzing and visualizing collecteddata. Examples of possible analysis and visualizationsincludes the presentation of lists ranking aspects bytheir importance of by their polarity values computedwithin the whole data repository. This kind of analysisenables, for instance, the discovery of product issues.

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