A survey on sentiment analysis in Urdu: A resource-poor language
Khattak, Asad; Zubair Asghar, Muhammad; Saeed, Anam; Hameed, Ibrahim A.; Asif Hassan, Syed; Ahmad, Shakeel
Peer reviewed, Journal article
Published version
View/ Open
Date
2020Metadata
Show full item recordCollections
- Institutt for IKT og realfag [597]
- Publikasjoner fra CRIStin - NTNU [38289]
Original version
https://doi.org/10.1016/j.eij.2020.04.003Abstract
Background/introduction
The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions. While the volume of studies conducted on sentiment analysis is rapidly expanding, these studies mostly address English language concerns. The primary goal of this study is to present state-of-art survey for identifying the progress and shortcomings saddling Urdu sentiment analysis and propose rectifications.
Methods
We described the advancements made thus far in this area by categorising the studies along three dimensions, namely: text pre-processing lexical resources and sentiment classification. These pre-processing operations include word segmentation, text cleaning, spell checking and part-of-speech tagging. An evaluation of sophisticated lexical resources including corpuses and lexicons was carried out, and investigations were conducted on sentiment analysis constructs such as opinion words, modifiers, negations.
Results and conclusions
Performance is reported for each of the reviewed study. Based on experimental results and proposals forwarded through this paper provides the groundwork for further studies on Urdu sentiment analysis.
Previous article in issueNext article in issue
Keywords
Urdu sentiment analysisPre-processingSentiment lexiconDatasetsCorpusUrdu sentiment classificationSemantic orientation