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Technical Approach in Text Mining for Stock Market Prediction: A Systematic Review

Mohammad Rabiul Islam, Imad Fakhri Al-Shaikhli, Rizal Bin Mohd Nor, Vijayakumar Varadarajan
2018 Indonesian Journal of Electrical Engineering and Computer Science  
Due to research significance, this empirical research also highlights the limitation of different strategies and methods on exact aspects of theoretical framework for enhancing of performance.  ...  Moreover, most sophisticated soft-computing methods and techniques are reviewed in terms of analysis, comparison and evaluation for its performance based on electronic textual data.  ...  ACKNOWLEDGEMENTS This research work was partially supported by International Islamic University Malaysia, FRGS14-127-0368 and ERGS13-018-0051 from Ministry of Higher Education of Malaysia.  ... 
doi:10.11591/ijeecs.v10.i2.pp770-777 fatcat:n5hf2opjczdfneo5lnhtg6eske

Sentiment Analysis Approaches on Different Data set Domain: Survey

Shailendra Kumar Singh, Sanchita Paul, Dhananjay Kumar
2014 International Journal of Database Theory and Application  
This paper focuses on the comparative study (1997 -2012) of different sentiment classification techniques performed on different data set domain such as web discourse, reviews and news articles etc.  ...  Sentiment classification of product and service reviews and comments has emerged as the most useful application in the area of sentiment analysis.  ...  They are machine learning algorithms, link analysis methods, and score-based approaches. Machine learning algorithms are applicable to sentiment analysis mostly belongs to supervised classification.  ... 
doi:10.14257/ijdta.2014.7.5.04 fatcat:ddphajpa4vhcvbj2dcfmsdlyoa

The Various Approaches for Sentiment Analysis: A Survey

2016 International Journal of Science and Research (IJSR)  
Sentiment analysis or Opinion mining is a machine learning approach in which machines analyze and classify the human's sentiments which are expressed in the form of either text or speech.  ...  The textual reviews available in the web are increasing day by day. Manual analysis of such large number of reviews is practically impossible.  ...  Semi-supervised learning makes use of unlabeled data for training -typically a small amount of labeled data with a large amount of unlabeled data. 2) The Lexicon-based Approach This approach completely  ... 
doi:10.21275/v5i1.nov152558 fatcat:dg7un5v43be2nkamnnnubeucwy

A survey on sentiment analysis in tourism

sarah anis, Sally Saad, Mostafa Aref
2020 International Journal of Intelligent Computing and Information Sciences  
Sentiment analysis is the practice of applying natural language processing, statistics and machine learning methods to extract and identify the common opinion behind the text in a review, blog discussion  ...  Tourism-related websites have turned into an incredible data source that impacts the tourism industry from many points of view.  ...  The commonly used approach for sentiment classification is supervised machine learning, it is well-known for its high accuracy, but they require a large amount of annotated training data which is costly  ... 
doi:10.21608/ijicis.2020.106309 fatcat:hhmnterlezaeriuyywoghhnpi4

A Literature Review on Application of Sentiment Analysis Using Machine Learning Techniques

Anvar Shathik J, Krishna Prasad K
2020 Zenodo  
Finally, this paper includes a research proposal for e-commerce environment towards sentiment analysis applying machine learning algorithms.  ...  This paper presents the common techniques of analyzing sentiment from a machine learning perspective.  ...  RESEARCH AGENDA : 1] What approaches and methods are better for classification? 2] What machine learning techniques can improve the performance evaluation of data?  ... 
doi:10.5281/zenodo.3977576 fatcat:djsvzgiypnfibcvj6swo3pw75u

Sentiment Analysis in the Era of Web 2.0: Applications, Implementation Tools and Approaches for the Novice Researcher

Mahmood Umar, Mansur Aliyu, Salisu Modi
2022 Caliphate Journal of Science and Technology  
Studies show that machine learning approaches result in large data sets on document-level sentiment classification.  ...  This study explores sentiment analysis of Web 2.0 for novice researchers to promote collaboration and suggest the best tools for sentiment data analysis and result efficiency.  ...  Also the effort of Department of Computer Science and its staff for their contributions in one way or the other is recognised.  ... 
doi:10.4314/cajost.v4i1.1 fatcat:gijymvnbnfe7neht65ksyg2uoi

A PANOPTICS OF SENTIMENTAL ANALYSIS

K. Venkata Raju
2017 International Journal of Advanced Research in Computer Science  
Sentimental analysis of Text data available in different forms of blogs, twitters, Facebook and Linked-in offers information to assess perspective of services of people's, products that are of their interest  ...  Sentiment Analysis(SA) persist to be a most significant research problem due to its immense applications, recognize the sentiment orientation of terms of sentiment which is the sentiment analysis fundamental  ...  Web data on movie and product web domain is gathered by means of web crawler applied diverse techniques of preprocessing evaluated using machine learning algorithm [8] hotel reviews from Trip Advisor  ... 
doi:10.26483/ijarcs.v8i7.4448 fatcat:o5anrkuknvdzfdn6275zdeyrsa

Behavior Prophecy of Stock Trader using Machine Learning Techniques

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Many Machine Learning (ML) methods and recognizable proof strategies are looked at and examined for stock trader behavior analysis. Their parameters are considered and enhancements are recommended.  ...  The vital segment examination is the classification and prediction technique used to recognize and understand the typical and irregular behavior of the stock trader.  ...  Section V contains the summary and directions for future enhancement. Behavior Prophecy of Stock Trader using Machine Learning Techniques B. N. Shankar Gowda, Vibha Lakshmikantha II.  ... 
doi:10.35940/ijitee.k2226.0981119 fatcat:mmtms5nik5d6xexxsabafc262m

Multi Class Data Classification to Improve Accuracy in Sentiment Analysis using Machine Learning

Daram Vishnu
2021 International Journal for Research in Applied Science and Engineering Technology  
Sentiment analysis is done using machine learning, where it requires training data and testing data to train a model.  ...  These days most of the sentiment analysis techniques divide the text into either binary or ternary classification in this paper we are classifying the movie reviews into 5 classes.  ...  MACHINE LEARNING METHODS USED A.  ... 
doi:10.22214/ijraset.2021.35291 fatcat:sf2atqorkrgsxbdqjo2xnqqh2e

Approaches, Tools and Applications for Sentiment Analysis Implementation

Alessia D'Andrea, Fernando Ferri, Patrizia Grifoni, Tiziana Guzzo
2015 International Journal of Computer Applications  
Keywords Sentiment analysis, Social Media, Machine-learning approach, Lexicon-based approach, Sentiment classification The sentiment classification approaches can be classified in: (i) machine learning  ...  The paper gives an overview of the different sentiment classification approaches and tools used for sentiment analysis.  ...  The machine learning approach is used for predicting the polarity of sentiments based on trained as well as test data sets.  ... 
doi:10.5120/ijca2015905866 fatcat:4jbg6w5kfrcfbn2xrufhkiqn6q

Performance Investigation of Feature Selection Methods [article]

Anuj sharma, Shubhamoy Dey
2013 arXiv   pre-print
This paper explores applicability of feature selection methods for sentiment analysis and investigates their performance for classification in term of recall, precision and accuracy.  ...  Sentiment analysis or opinion mining has become an open research domain after proliferation of Internet and Web 2.0 social media.  ...  This paper investigates performance of different feature selection methods from data mining research for the purpose of sentiment based classification.  ... 
arXiv:1309.3949v1 fatcat:2irqbsvb2ngblf5qflxvwttp5y

Enhancing The Sentiment Classification Accuracy Of Twitter Data Using Machine Learning Algorithms

Muthukumar Bhuvaneswari1, Vasudevan Srividhya2
2017 Zenodo  
After the polarity classification two machine learning algorithms are employed to enhance the accuracy of sentiment classification.  ...  The main aim of this work is to classify the sentiment of twitter data using machine learning algorithms.  ...  The proposed research work is undertaken to enhance the Sentiment classification accuracy of twitter data using machine learning algorithms.  ... 
doi:10.5281/zenodo.263017 fatcat:ufh7lxpfnbbwdemzw27suwzx54

ACCURACY IN BINARY, TERNARY AND MULTI-CLASS CLASSIFICATION SENTIMENTAL ANALYSIS-A SURVEY

Anjume Shakir
2018 International Journal of Advanced Research in Computer Science  
Sentiment analysis is nowadays quite a hot topic for research.  ...  The Binary and Ternary classification is not going to serve the sole purpose of sentimental analysis. Multi-Class classification can help in getting the essence and core message from the data.  ...  APPROACH The proposed work is based on data comparison of the accuracy achieved in case of different class sentimental analysis which has been achieved till now using different machine learning techniques  ... 
doi:10.26483/ijarcs.v9i2.5866 fatcat:yrmtkcc2jvcxfiuvriciiteaoq

LDA-based Topic Modelling in Text Sentiment Classification: An Empirical Analysis

Aytug Onan, Serdar Korukoglu, Hasan Bulut
2016 International Journal of Computational Linguistics and Applications  
Web is a rich and progressively expanding source of information. Sentiment analysis can be modelled as a text classification problem.  ...  Sentiment analysis is the process of identifying the subjective information in the source materials towards an entity. It is a subfield of text and web mining.  ...  (3) Which configuration of classification algorithms, ensemble learning methods, number of latent topics yield promising results for text sentiment classification?  ... 
dblp:journals/ijcla/OnanKB16 fatcat:66hf5uek5ndjpbal624muja6mm

Opinion mining for national security: techniques, domain applications, challenges and research opportunities

Noor Afiza Mat Razali, Nur Atiqah Malizan, Nor Asiakin Hasbullah, Muslihah Wook, Norulzahrah Mohd Zainuddin, Khairul Khalil Ishak, Suzaimah Ramli, Sazali Sukardi
2021 Journal of Big Data  
Most of the study addressed methods including machine learning, lexicon-based approach, hybrid approach, and Kansei approach in mining the sentiment and emotion based on text.  ...  The possible societal impacts of the current opinion mining technique, including machine learning and the Kansei approach, along with major trends and challenges, are highlighted.  ...  The authors fully acknowledge UPNM and MOHE for the approved fund, which made this research viable and effective.  ... 
doi:10.1186/s40537-021-00536-5 pmid:34900516 pmcid:PMC8642766 fatcat:gnbhgoafnngkzdyjspvrqqgxli
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