Quotation Weichselbraun, Albert, Gindl, Stefan, Fischer, Fabian, Vakulenko, Svitlana, Scharl, Arno. 2017. Aspect-Based Extraction and Analysis of Affective Knowledge from Social Media Streams. IEEE Intelligent Systems 32 (3), 80-88.


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Abstract

Extracting and analyzing affective knowledge from social media in a structured manner is a challenging task. Decision makers require insights into the public perception of a company's products and services, as a strategic feedback channel to guide communication campaigns, and as an early warning system to quickly react in the case of unforeseen events. The approach presented in this article goes beyond bipolar metrics of sentiment. It combines factual and affective knowledge extracted from rich public knowledge bases to analyze emotions expressed toward specific entities (targets) in social media. The authors obtain common and common-sense domain knowledge from DBpedia and ConceptNet to identify potential sentiment targets. They employ affective knowledge about emotional categories available from SenticNet to assess how those targets and their aspects (such as specific product features) are perceived in social media. An evaluation shows the usefulness and correctness of the extracted domain knowledge, which is used in a proof-of-concept data analytics application to investigate the perception of car brands on social media in the period between September and November 2015.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal IEEE Intelligent Systems
Citation Index SCI
Language English
Title Aspect-Based Extraction and Analysis of Affective Knowledge from Social Media Streams
Volume 32
Number 3
Year 2017
Page from 80
Page to 88
Reviewed? Y
URL http://ieeexplore.ieee.org/abstract/document/7933922/
DOI http://dx.doi.org/10.1109/MIS.2017.57

Associations

Projects
uComp (Embedded Human Computation for Knowledge Extraction and Evaluation)
People
Fischer, Fabian (Former researcher)
Vakulenko, Svitlana (Details)
External
Gindl, Stefan (MODUL University Vienna, Austria)
Scharl, Arno (MODUL University Vienna, Austria)
Weichselbraun, Albert (University of Applied Sciences Chur, Switzerland)
Organization
Applied Information Technology (Details)
Research areas (Ă–STAT Classification 'Statistik Austria')
1122 Artificial intelligence (Details)
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