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Sentiment Classification in Bangla Textual Content: A Comparative Study
[article]
2020
arXiv
pre-print
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Another important limitation, in the current literature for Bangla, is the absence of comparable results due to the lack of a well-defined train/test split. ...
Furthermore, we created a weighted list of lexicon content based on the valence score per class. We then analyzed the content for high significance entries per class, in the datasets. ...
Conclusions In this study, we have conducted comparative experiments using different annotated sentiment datasets consisting of Bangla content from social media for multiple domains. ...
arXiv:2011.10106v1
fatcat:zq5nsekikrhkld3wulovgevzu4
Table of Contents
2020
2020 11th International Conference on Electrical and Computer Engineering (ICECE)
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A RNN Based Parallel Deep Learning Framework for Detecting Sentiment Polarity from Twitter Derived Textual Data Design and Performance Analysis of A Low Power, Low Noise 1.6GHz Charge Pump Integer-N PLL ...
Content Categorization Using Supervised
Based Machine Learning Methods and Natural Language
Processing in Bangla Language
270-273
802
Aperture Averaged BER Performance Analysis of a non-
Hermitian ...
doi:10.1109/icece51571.2020.9393161
fatcat:q3dcoc3j45ekfptwd6oahgq3xe
Identifying vulgarity in Bengali social media textual content
2021
PeerJ Computer Science
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Besides, the analysis reveals that vulgarity is highly correlated with negative sentiment in social media comments. ...
In this paper, we provide the first comprehensive analysis on the presence of vulgarity in Bengali social media content. ...
DISCUSSION The results show that the sentiment lexicon yields poor performance in identifying vulgarity in Bengali textual content, as shown by its poor performance in both datasets. ...
doi:10.7717/peerj-cs.665
pmid:34805498
pmcid:PMC8576541
fatcat:ahhpekpg3zcntmdwsyuf7pznza
Bangla Text Classification using Transformers
[article]
2020
arXiv
pre-print
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In this work, we fine-tune multilingual transformer models for Bangla text classification tasks in different domains, including sentiment analysis, emotion detection, news categorization, and authorship ...
Text classification has been one of the earliest problems in NLP. ...
The study in [28] , provides a comparative analysis using both classical -SVM, and deep learning algorithms -LSTM and CNN, for sentiment classification in Bangla news comments. ...
arXiv:2011.04446v1
fatcat:2l7qbtqntvcd3mbzo3njds2gde
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla
[article]
2022
arXiv
pre-print
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In this work, we introduce BanglaBERT, a BERT-based Natural Language Understanding (NLU) model pretrained in Bangla, a widely spoken yet low-resource language in the NLP literature. ...
We are making the models, datasets, and a leaderboard publicly available at https://github.com/csebuetnlp/banglabert to advance Bangla NLP. ...
Single-Sequence Classification Sentiment classification is perhaps the most-studied Bangla NLU task, with some of the earlier works dating back over a decade (Das and Bandyopadhyay, 2010) . ...
arXiv:2101.00204v4
fatcat:l3u5thti6nar5folnd6ljyzf3i
Sentiment Analysis on Bangla and Romanized Bangla Text (BRBT) using Deep Recurrent models
[article]
2016
arXiv
pre-print
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Therefore, we first tried to provide a textual dataset - that includes not just Bangla, but Romanized Bangla texts as well, is substantial, post-processed and multiple validated, ready to be used in SA ...
Sentiment Analysis (SA) is an action research area in the digital age. ...
BACKGROUND
A. Sentiment Analysis A key point of our work is Sentiment Analysis, on Bangla (and Romanized Bangla) language. ...
arXiv:1610.00369v2
fatcat:eok2lmiu4vdpthu43wgkrfftf4
Sentiment Analysis Using Deep Learning Techniques: A Review
2017
International Journal of Advanced Computer Science and Applications
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of sentiment analysis such as sentiment classification, cross lingual problems, textual and visual analysis and product review analysis, etc. ...
The challenge for sentiment analysis is lack of sufficient labeled data in the field of Natural Language Processing (NLP). ...
Deep Neural Networks (DNN) In this study [32] , author has proposed a model for sentiment analysis considering both visual and textual contents of social networks. ...
doi:10.14569/ijacsa.2017.080657
fatcat:us4hwclsx5ghtjo4v5vkvfkqqm
A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models
[article]
2021
arXiv
pre-print
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In this study, we first provide a review of Bangla NLP tasks, resources, and tools available to the research community; we benchmark datasets collected from various platforms for nine NLP tasks using current ...
We provide comparative results for the studied NLP tasks by comparing monolingual vs. multilingual models of varying sizes. ...
Emotion Classification The work in emotion classification is relatively sparse compared to sentiment classification for Bangla content. To this effect, Das et al. ...
arXiv:2107.03844v3
fatcat:hermrinleneercodguko6kwxhu
Bangla Text Sentiment Analysis Using Supervised Machine Learning with Extended Lexicon Dictionary
2021
Natural Language Processing Research
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A B S T R A C T With the proliferation of the Internet's social digital content, sentiment analysis (SA) has gained a wide research interest in natural language processing (NLP). ...
Firstly, a specific domain-based categorical weighted lexicon data dictionary (LDD) is developed for analyzing sentiments in Bangla. ...
1.INTRODUCTION Sentiment analysis (SA), also called opinion mining [1] , is a field of study that predicts polarity in public opinion or textual data from microblogging sites [2] on a well-publicized ...
doi:10.2991/nlpr.d.210316.001
fatcat:m6vntop5vjbfzmz55ufvthppqm
Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods
2022
IEEE Access
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The studies are mainly concentrated on the specific domains of BNLP, such as sentiment analysis, speech recognition, optical character recognition, and text summarization. ...
Therefore, in this paper, we present a thorough analysis of 75 BNLP research papers and categorize them into 11 categories, ...
The proposed method was compared with different classifiers which show good performance analysis. However, the paper contained a classification of only two sentiment classes. ...
doi:10.1109/access.2022.3165563
fatcat:rmersduz6vbyjjczvobrebskmi
Similarity of Trending News A Case Study of Bangladesh
2021
International Journal of Research Publications
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All the Bangla news exists on social media is in textual format which is unstructured as well. ...
As there are lack of analysis regarding Bangla news of Facebook posts have been introduced, present study looks for drawing a pattern that refers a constructive knowledge from huge amount of data. ...
Therefore, it is obvious that a huge umber of bangla contents are shared everyday by social media users and among those newspaper contents are very common where the source of these contents are undoubtedly ...
doi:10.47119/ijrp100731320211831
fatcat:tstqh2noxnbbtnzoir6uhe4cd4
Bangla Natural Language Processing: A Comprehensive Review of Classical, Machine Learning, and Deep Learning Based Methods
[article]
2021
arXiv
pre-print
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There is an apparent scarcity of resources that contain a comprehensive study of the recent BNLP tools and methods. ...
Many efforts are also ongoing to make it easy to use the Bangla language in the online and technical domains. ...
[67] described their implementation of sentiment polarity detection in Bangla Tweets. They used the Bangla tweet dataset released for SAIL content 2015. ...
arXiv:2105.14875v2
fatcat:kvqmgxpthvh2fj7jza64n6kaiq
Multimodal Hate Speech Detection from Bengali Memes and Texts
[article]
2022
arXiv
pre-print
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Our study suggests that memes are moderately useful for hate speech detection in Bengali, but none of the multimodal models outperform unimodal models analyzing only textual data. ...
Like English, Bengali social media content also includes images along with texts (e.g., multimodal contents are posted by embedding short texts into images on Facebook), only the textual data is not enough ...
In a recent approach [2] , Karim et al. provided classification benchmarks for document classification, sentiment analysis, and hate speech detection for Bengali. ...
arXiv:2204.10196v1
fatcat:ryboqcmyqfd6dcv3q5qjpiz23q
Using Machine Learning to Detect Events on the Basis of Bengali and Banglish Facebook Posts
2021
Electronics
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In modern times, ensuring social security has become the prime concern for security administrators. ...
For evaluating the effectiveness of our proposed model more precisely, we compared it with two other classifiers: Support Vector Machine and Decision Tree. ...
They unitedly engaged the textual, visual, and social content in microblog evaluation for truly exploring the inherent interrelation among the diverse data. Shi et al. ...
doi:10.3390/electronics10192367
fatcat:2rdsvzfgnberhkpu7kfa2flwta
Opinion mining on newspaper headlines using SVM and NLP
2019
International Journal of Electrical and Computer Engineering (IJECE)
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<p>Opinion Mining also known as Sentiment Analysis, is a technique or procedure which uses Natural Language processing (NLP) to classify the outcome from text. ...
Multiple research have been done in opinion mining for online blogs, Twitter, Facebook etc. ...
INTRODUCTION Opinion Mining or Sentiment Analysis is a task to analyze opinions or sentiments from textual data. It is useful in analyzing NLP applications. ...
doi:10.11591/ijece.v9i3.pp2152-2163
fatcat:oodcrnigkzbnfcfxpqsnh2qiui
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