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A novel classification approach based on Naïve Bayes for Twitter sentiment analysis

2017 KSII Transactions on Internet and Information Systems  
In the existing sentiment analysis based on the Naïve Bayes algorithm, a same number of attributes is usually employed to estimate the weight of each class.  ...  As a result, huge amount of data are generated from SNS such as Twitter, and sentiment analysis of SNS data is very important for various applications and services.  ...  Conclusion In this paper a novel attribute weighting and feature selection approach for Twitter sentiment analysis have been presented based on Naïve Bayes.  ... 
doi:10.3837/tiis.2017.06.011 fatcat:mv6rg7oxf5gchf7omm6dnee66i

Sentiment Analysis: A Survey

Suman Rani
2017 International Journal for Research in Applied Science and Engineering Technology  
This paper describes the study of different sentiment analysis methods on different web resources such as review sites, blogs, discussion forums and news.  ...  Social networking sites such as Twitter, Facebook etc are rich in comments, customer reviews, opinion and sentiments.  ...  Rights are Reserved Shoiab Ahmed and Ajit Danti [24] A Novel Approach for Sentiment Analysis and Opinion Mining based on SentiwordNet using Web Data Unsupervised approach using SWN Web data  ... 
doi:10.22214/ijraset.2017.8276 fatcat:za7tqrlbhfhoxkiyh4lf23mkau

An Evaluation of Sentiment Analysis and Classification Algorithms for Arabic Textual Data

Ayman Mohamed
2017 International Journal of Computer Applications  
Different algorithms of sentiment analysis and classifications are evaluated based on their use in Arabic language which has not been evaluated before.  ...  A comparison table for the proposed algorithms is presented that explains each algorithm and its use in mining and analysis of Arabic textual data and provides different evaluation for each sentiment analysis  ...  and Arabic tweets: A systematic literature review," Journal of Theoretical and Applied Information Technology, vol. 56, p. [338][339][340][341][342][343][344][345][346][347][348] 2013  ... 
doi:10.5120/ijca2017912770 fatcat:da32p7265fbitjwawtp3ozkrvq

Twitter Sentiment Analysis on Government Law Using Real Time Data

Sujata Patil, Bhavesh Wagh, Aditya Bhinge, Aakash Sahal, Prof. Madhav Ingale
2021 International Journal of Scientific Research in Science and Technology  
This paper-based is on social media Twitter datasets of particular schemes and their polarity of sentiments. The popularity of the Internet has been rapidly increased.  ...  This Sentiment analysis and opinion mining research is a hot research area that comes under Natural Language processing.  ...  Here, an open-source approach for text mining and sentiment analysis using a set of R packages for mining Twitter data and sentiment analysis is presented, which is applicable for other social media sites  ... 
doi:10.32628/ijsrst218611 fatcat:hfccxe4cdvhmxlrgnrno3oaqge


P. Bavithra Matharasi
2018 International Journal of Advanced Research in Computer Science  
In this work, unigram and bigram approach are combined together to form novel model that uses Naïve Bayes approach and results were found. This novel approach gave a better result.  ...  Twitter is the most popular social media today. It is the biggest platform for communication. In this research, tweets from twitter is taken for sentiment analysis.  ...  TWITTER DATA The goal of this paper is to implement a novel method that uses Naïve Bayes approach and find the result for accuracy. Many researchers had worked on domain specific sentiment analysis.  ... 
doi:10.26483/ijarcs.v9i1.5346 fatcat:tahlsrcxufecvchqbe6ayorcna

Machine Learning-Based Sentiment Analysis for Twitter Accounts

Ali Hasan, Sana Moin, Ahmad Karim, Shahaboddin Shamshirband
2018 Mathematical and Computational Applications  
Despite the use of various machine-learning techniques and tools for sentiment analysis during elections, there is a dire need for a state-of-the-art approach.  ...  Moreover, this paper also provides a comparison of techniques of sentiment analysis in the analysis of political views by applying supervised machine-learning algorithms such as Naïve Bayes and support  ...  Figure 1 . 1 (a) Framework of tweet classification and sentiment analysis; (b) framework of tweet classification and sentiment analysis.  ... 
doi:10.3390/mca23010011 fatcat:fdu2d6cshrc7tiwnrpluhnfd44

Controversial Analysis:- Sentimental Analysis of Twitter Data

Samarth Jaykar Shetty, Badal Rakesh Thosani, Lenherd Deon Olivera, Supriya Kamoji
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Controversial analysis deals with identifying and classifying opinions or sentiments expressed in source text. We present a novel approach for naturally ordering the sentiments of Twitter messages.  ...  We show the consequences of machine learning algorithm for classifying the sentiment of Twitter messages utilizing a novel feature vector.  ...  Naïve Bayes Naive Bayes is a simple model which works well on text categorization [5] . use a multinomial Naive Bayes model.  ... 
doi:10.23956/ijarcsse/v7i4/0124 fatcat:admxhugvefd5pn3zbhp6rxtvve

Opinion Mining and Sentiment Analysis

Bo Pang, Lillian Lee
2008 Foundations and Trends in Information Retrieval  
This approach is novel in the sense that ESA has not been used for Sentiment Analysis in the literature, to the best of our knowledge.  ...  We implemented a combination of Explicit Semantic Analysis (ESA) with Naive Bayes classifier.  ...  Conclusion We presented an approach of using ESA for sentiment classification. The submitted system follow a combination of standard Naive Bayes model and ESA based classification.  ... 
doi:10.1561/1500000011 fatcat:o5ktuwpyiffupor3kr3lj272hu

Philippine Twitter Sentiments during Covid-19 Pandemic using Multinomial Naïve-Bayes

John Pierre D
2020 International Journal of Advanced Trends in Computer Science and Engineering  
A total of 29,514 tweets were collected throughout the said dates, where 10% of which was manually labeled to train a Multinomial Naive Bayes classification model that achieved 72% accuracy.  ...  This paper examines the polarity of COVID -19 related opinions on Twitter from January to March 2020 by applying natural language processing.  ...  [16] published a paper that includes a description of Feature Extraction and its importance on classification models, especially for Naïve Bayes.  ... 
doi:10.30534/ijatcse/2020/6491.32020 fatcat:iu6dalheizfhxpese5s3gwh5ou

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 sentiment analysis finds its application in movie reviews, blogs, customer feedback, twitter etc.  ...  They investigated the utility of Naïve Bayes and SVMs on a novel collection of datasets created from web log posts.  ... 
doi:10.21275/v5i1.nov152558 fatcat:dg7un5v43be2nkamnnnubeucwy

Feature Extraction for Sentiment Classification on Twitter Data

2016 International Journal of Science and Research (IJSR)  
In this paper, we introduce a novel approach for automatically classifying the sentiment of "tweets" into positive, negative and neutral sentiment.  ...  People post real time messages about their opinions on different topics, discuss current issues, complain, and express positive sentiment for products they use in daily life.  ...  In [13] , author did a magnificent job for sentiment classification on Twitter data.  ... 
doi:10.21275/v5i2.nov161677 fatcat:zi4hiof3ljhy5eyylszjvwpmbm

Twitter Sentiment Analysis: A Political View

Joylin Priya Pinto
2020 International Journal of Advanced Trends in Computer Science and Engineering  
It involves an application of sentiment analysis on naturally written language to extract sentiments conveyed by the users. Twitter sentiment analysis is demanding.  ...  Twitter is a famous micro-blogging service for tracking public mood with respect to an object or entity.  ...  [2] focused on three supervised learning algorithms namely SVM, Naïve Bayes and maximum entropy for the twitter data classification. Tweets are classified based on the expressed sentiments.  ... 
doi:10.30534/ijatcse/2020/103912020 fatcat:ry26yqezqnhnxfsk3hlpcshubq

SVM and Naïve Bayes Classification Ensemble Method for Sentiment Analysis

Konstantinas Korovkinas, Paulius Danėnas
2017 Baltic Journal of Modern Computing  
In this paper we introduce a new method to improve classification performance in sentiment analysis, by combining SVM and Naïve Bayes classification results to recognize positive or negative sentiment,  ...  It was observed that better results were obtained using our proposed method in all the experiments, compared to simple SVM and Naïve Bayes classification.  ...  Catal and Nangir (2017) proposed a novel sentiment classification technique based on Vote ensemble classifier utilizes from three individual classifiers: Bagging, Naïve Bayes, and Support Vector Machines  ... 
doi:10.22364/bjmc.2017.5.4.06 fatcat:co63q4nmfbhnjh4gwcflls2j2q

Exploration of Twitter Sentiments and Classification by using Deep CNN and Naive Bayes

2020 International journal of recent technology and engineering  
In the preceding paper which used usnsupervised learning approach for classification, has an accuracy of 87% and supervised has an accuracy of 89%.  ...  It has a higher performance on the accuracy, precision and recall.  ...  ACKNOWLEDGEMENT We acknowledge this open way to offer our certifiable gratitude to all those without whom this project would not have been a success.  ... 
doi:10.35940/ijrte.b3963.079220 fatcat:ya4wko2llvevxi7xde4ntkmpjm

Sentiment Analysis of the Covid-19 Virus Infection in Indonesian Public Transportation on Twitter Data: A Case Study of Commuter Line Passengers

Intania Cahya Sari, Yova Ruldeviyani
2020 2020 International Workshop on Big Data and Information Security (IWBIS)  
Furthermore, the result of sentiment analysis was a positive classification compared to the other 2 classes.  ...  This research was implemented using a comparison of 2 methods, Naïve Bayes outperformed the Decision Tree with an accuracy of 73.59%.  ...  Naïve Bayes was also selected based on a survey that had been conducted, which is about the use of an algorithm that will be used in sentiment analysis.  ... 
doi:10.1109/iwbis50925.2020.9255531 dblp:conf/iwbis/SariR20 fatcat:3wochrrb3jgcfig3evag7x2bju
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