Authors:
Raheleh Makki
;
Stephen Brooks
and
Evangelos E. Milios
Affiliation:
Dalhousie University, Canada
Keyword(s):
Context-Dependent Sentiment Lexicon, Visualization, User Interaction.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
Text and Document Visualization
;
Usability Studies and Visualization
;
Visualization Applications
Abstract:
One of the important factors in the performance of sentiment analysis methods is having a comprehensive
sentiment lexicon. However, since sentiment words have different polarities not only in different domains,
but also in different contexts within the same domain, constructing such context-specific sentiment lexicons
is not an easy task. The high costs of manually constructing such lexicons motivate researchers to create
automatic methods for finding sentiment words and assigning their polarities. However, existing methods may
encounter ambiguous cases with contradictory evidence which are hard to automatically resolve. To address
this problem, we aim to engage the user in the process of polarity assignment and improve the quality of
the generated lexicon via minimal user effort. A novel visualization is employed to present the results of
the automatic algorithm, i.e., the extracted sentiment pairs along with their polarities. User interactions are
provided to facilitate the supervi
sion process. The results of our user study demonstrate (1) involving the
user in the polarity assignment process improves the quality of the generated lexicon significantly, and (2)
participants in the study preferred our visual interface and conveyed that it is easier to use compared to a
text-based interface.
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