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Deep Learning and Machine Learning-Based Model for Conversational Sentiment Classification

Sami Ullah, Muhammad Ramzan Talib, Toqir A. Rana, Muhammad Kashif Hanif, Muhammad Awais
2022 Computers Materials & Continua  
Once the dataset is prepared, we have used different deep learning and machine learning techniques for the classification of emotion.  ...  Therefore, in this paper, we have proposed a model which utilizes deep learning and machine learning approaches for the classification of users' emotions from the text.  ...  The overall polarity of the sentence was calculated with the help of a rule-based technique for the classification of sentiments with the help of calculated polarity, discourse relation, and polarity relation  ... 
doi:10.32604/cmc.2022.025543 fatcat:6cuba7o63bbcxhsjt6vsucuj4a

Roman Urdu News Headline Classification Empowered With Machine Learning

Muhammad Adnan Khan, Rizwan Ali Naqvi, Nauman Malik, Shazia Saqib, Tahir Alyas, Dildar Hussain
2020 Computers Materials & Continua  
English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply of Roman Urdu in the past.  ...  The complexities associated with Roman Urdu include the non-availability of the tagged corpus, lack of a set of rules, and lack of standardized spellings.  ...  [Sharf and Rahman (2018) ] created discourse parser for Roman Urdu. A lexicon-based approach is also used for sentence-level sentiment analysis [Hashim and Khan (2016) ].  ... 
doi:10.32604/cmc.2020.011686 fatcat:6uwfboml3ffaxnpiamvctdhaia

A Review of Urdu Sentiment Analysis with Multilingual Perspective: A Case of Urdu and Roman Urdu Language

Ihsan Ullah Khan, Aurangzeb Khan, Wahab Khan, Mazliham Mohd Su'ud, Muhammad Mansoor Alam, Fazli Subhan, Muhammad Zubair Asghar
2021 Computers  
Our research focused on collecting research papers related to Urdu and Roman Urdu language and analyzing them in terms of preprocessing, feature extraction, and classification techniques.  ...  Based on results obtained and the comparisons made, we suggested some helpful steps in a future study.  ...  Future Work We aim to develop a unique classifier for detecting sentiments in product reviews in Roman Urdu and pure Urdu, then extend the work to local languages, such as Sarakai and Punjabi.  ... 
doi:10.3390/computers11010003 fatcat:qd5jq5zutbbphbxgnshvip4sky

UTSA: Urdu Text Sentiment Analysis Using Deep Learning Methods

Uzma Naqvi, Abdul Majid, S. Ali Abbas
2021 IEEE Access  
ACKNOWLEDGMENTS The authors would like to thank the editor and anonymous reviewers for their perceptive comments and suggestions.  ...  [26] identified sub-opinions by using discourse information which they then fed to rule-based and supervised methods.  ...  They discovered that ML methods outperform rule-based methods if training data is available; otherwise, rule-based methods are a better choice for sentiment classification.  ... 
doi:10.1109/access.2021.3104308 fatcat:uk2m3twgsfeupmcxvkk7z3jwkm

Sentiment Analysis of Roman Urdu on E-Commerce Reviews Using Machine Learning

Bilal Chandio, Asadullah Shaikh, Maheen Bakhtyar, Mesfer Alrizq, Junaid Baber, Adel Sulaiman, Adel Rajab, Waheed Noor
2022 CMES - Computer Modeling in Engineering & Sciences  
The primary objective of this study is to investigate the diverse machine learning methods for the sentiment analysis of Roman Urdu data which is very informal in nature and needs to be lexically normalized  ...  Moreover, a series of experiments are conducted on diverse machine learning and deep learning models to compare the performance with our proposed model.  ...  In a recent study the role of discourse information for Urdu SA is also studied [42] .  ... 
doi:10.32604/cmes.2022.019535 fatcat:ppatw6oynzh4lnbkpq4ej2syfe

A survey on sentiment analysis in Urdu: A resource-poor language

Asad Khattak, Muhammad Zubair Asghar, Anam Saeed, Ibrahim A. Hameed, Syed Asif Hassan, Shakeel Ahmad
2020 Egyptian Informatics Journal  
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.  ...  Based on experimental results and proposals forwarded through this paper provides the groundwork for further studies on Urdu sentiment analysis. Ó 2020 THE AUTHORS.  ...  This Research work was supported by Zayed University Research Incentives Fund#R18052, co-funded by Norwegian university of science and technology, Ålesund, Norway.  ... 
doi:10.1016/j.eij.2020.04.003 fatcat:qvymechpvnhypg2telxbs4wj4m

DISCOURSE BASED OPINION MINING ON ROMAN URDU DATA

Zareen Sharaf, Szabist, Karachi, Pakistan, Husnain Manzoor Ali
2019 Journal of Independent Studies and Research - Computing  
Analysis and Classification for Roman Urdu.  ...  The use of Roman Urdu (in the form of web and user-generated content) is a common mode of communication on social media.  ...  Better results can be achieved by introducing more enhanced rules and other machine learning techniques.  ... 
doi:10.31645/jisrc-019-04 fatcat:hlkbytb4e5hevcsmt3fblqkgvi

Mining opinion components from unstructured reviews: A review

Khairullah Khan, Baharum Baharudin, Aurnagzeb Khan, Ashraf Ullah
2014 Journal of King Saud University: Computer and Information Sciences  
Because of the huge number of reviews in the form of unstructured text, it is impossible to summarize the information manually.  ...  Opinion mining is a way to retrieve information through search engines, Web blogs and social networks.  ...  on the accuracy of machine-learning techniques for polarity classification.  ... 
doi:10.1016/j.jksuci.2014.03.009 fatcat:oma2lylgpzc7noalvewtsbtdqa

Establishing News Credibility using Sentiment Analysis on Twitter

Zareen Sharf, Zakia Jalil, Wajiha Amir, Nudrat Siddiqui
2019 International Journal of Advanced Computer Science and Applications  
The widespread use of Internet has resulted in a massive number of websites, blogs and forums.  ...  Sentiment Analysis or Opinion Mining is the system that intelligently performs classification of sentiments by extracting those opinions or sentiments from the given text (or comments or reviews).  ...  Most of the Twitter sentiment analysis is done using machine learning approach.  ... 
doi:10.14569/ijacsa.2019.0100927 fatcat:a72n2hxzbvgozerfx5ixz3as7i

Over a Decade of Social Opinion Mining [article]

Keith Cortis, Brian Davis
2020 arXiv   pre-print
Such multi-source information fusion plays a fundamental role in mining of people's social opinions from social media platforms.  ...  A thorough systematic review was carried out on Social Opinion Mining research which totals 485 studies and spans a period of twelve years between 2007 and 2018.  ...  ), for sentiment classification of Twitter datasets; and Statistical-based (7.8%), Machine Learning and Statistical-based (7.4%), and Lexicon, Machine Learning and Statistical-based (7.4%) techniques  ... 
arXiv:2012.03091v1 fatcat:bm5nydbdvbalzi33l3w2ivkdja

Identification of HATE speech tweets in Pashto language using Machine Learning techniques

2021 International Journal of Advanced Trends in Computer Science and Engineering  
As in different languages procreation of hate speech has compelling and symbolic consideration on social media. Hate speech has a great impact on society, using hate words harms others dignity.  ...  Most of the research work has been done in this domain for other languages, and it's very maturein the context of detecting hate speech.  ...  If it is needed to extract some important information from a document this method of TF-IDF increases the proportion of words appearing in the document.  ... 
doi:10.30534/ijatcse/2021/021032021 fatcat:upkdqfspu5agzk6d73asmd3yqi

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
Learning-based Multi-Sieve Co-reference Resolution with Knowledge Lev Ratinov and Dan Roth Saturday 11:00am-11:30am -202 A (ICC) We explore the interplay of knowledge and structure in co-reference resolution  ...  Compared with the best system from CoNLL-2011, which employs a rule-based method, our system shows competitive performance.  ...  , which incorporates rule-based and statistic-based techniques.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

Sentiment Analysis for Fake News Detection

Miguel A. Alonso, David Vilares, Carlos Gómez-Rodríguez, Jesús Vilares
2021 Electronics  
In recent years, we have witnessed a rise in fake news, i.e., provably false pieces of information created with the intention of deception.  ...  This has led to sentiment analysis, the part of text analytics in charge of determining the polarity and strength of sentiments expressed in a text, to be used in fake news detection approaches, either  ...  Hybrid techniques were also considered, in particular an expert-crowdsource approach that combined two methods of manual fact-checking and a human-machine approach that combined machine learning algorithms  ... 
doi:10.3390/electronics10111348 fatcat:p34nbmtkzrcqrowu24nmu4axnq

Sentiment Analysis and Opinion Mining [chapter]

Lei Zhang, Bing Liu
2017 Encyclopedia of Machine Learning and Data Mining  
Instead of using a standard machine learning method, researchers have also proposed several custom techniques specifically for sentiment classification, e.g., the score function in (Dave, Lawrence and  ...  In , the discourse information within a single compound sentence was used to perform sentiment classification of the sentence.  ... 
doi:10.1007/978-1-4899-7687-1_907 fatcat:iy5ty44cyzbrtodxfo7osy3iu4

A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios [article]

Michael A. Hedderich, Lukas Lange, Heike Adel, Jannik Strötgen, Dietrich Klakow
2021 arXiv   pre-print
A goal of our survey is to explain how these methods differ in their requirements as understanding them is essential for choosing a technique suited for a specific low-resource setting.  ...  After a discussion about the different dimensions of data availability, we give a structured overview of methods that enable learning when training data is sparse.  ...  Mayhew et al. (2017), Fang and techniques or to provide labeling rules.  ... 
arXiv:2010.12309v3 fatcat:26dwmlkmn5auha2ob2qdlrvla4
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