Recognizing sentimental emotions in text by using Machine Learning

Recognizing sentimental emotions in text by using Machine Learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Bibliografiset tiedot
Päätekijät:	Bushra, Tabassum Khan, Saha, Kallol, Mulki, Ammin Hossain, Khan, Sanjana Sabah, Binta Amzad, Afrin
Muut tekijät:	Mostakim, Moin
Aineistotyyppi:	Opinnäyte
Kieli:	English
Julkaistu:	Brac University 2023
Aiheet:	BERT Bag of Words TF-IDF Naive Bayes LSTM Machine learning
Linkit:	http://hdl.handle.net/10361/18070

Samankaltaisia teoksia

Text classification with an efficient preprocessing technique for cross-language and multilingual data
Tekijä: Khan, Towhid, et al.
Julkaistu: (2023)

Multimodal fake news detection using text and image
Tekijä: Biswas, Trisha, et al.
Julkaistu: (2024)

A document vectorization approach to Resume Ranking System(RRS)
Tekijä: Nabi, Norun
Julkaistu: (2023)

Utilization of machine learning classifiers to predict different forms of mental illness: schizophrenia, PTSD, bipolar disorder and depression
Tekijä: Jaman, Ayman Ibn, et al.
Julkaistu: (2021)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
Tekijä: Shourin, Bushra, et al.
Julkaistu: (2018)

Predicting subject area interest of a student using naive bayes
Tekijä: Hossain, Shakib
Julkaistu: (2016)

FakeDetect: Bangla fake news detection model based on different machine learning classifiers
Tekijä: Sraboni, Tasnuba, et al.
Julkaistu: (2021)

Entrepreneural growth of bean bags and it’s future in Bangladesh
Tekijä: Zaman, Fahim
Julkaistu: (2020)

An effective machine learning approach for sentiment analysis of restaurant reviews
Tekijä: Karim, Rabita
Julkaistu: (2018)

Optimizing restaurant recommendations through sentiment analysis
Tekijä: Juha, Tasnia, et al.
Julkaistu: (2024)

No government steps so far proved effective to stop the use of banned polythene bags, which are harmful for the environment: how to stop it?
Tekijä: The New Age
Julkaistu: (2016)

Sentiment analysis in Bengali Text using NLP
Tekijä: Sarkar, Ankon, et al.
Julkaistu: (2023)

Identification of childhood leukemia using deep learning
Tekijä: Tultul, Farana Naz
Julkaistu: (2018)

Predicting suicidal intent from social media text post using machine learning
Tekijä: Chowdhury, Md. Mubin Ul Islam, et al.
Julkaistu: (2023)

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
Tekijä: Rabbi, Md. Nafis
Julkaistu: (2024)

Sentimental analysis of food review contents to improve food culture and the quality of virtual content using natural language processing and machine learning
Tekijä: Sarkar, Ripa, et al.
Julkaistu: (2024)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
Tekijä: Mouli, Nazifa, et al.
Julkaistu: (2023)

Virtual teaching assistant for undergraduate students using natural language processing & deep learning
Tekijä: Sakib, Sadman Jashim, et al.
Julkaistu: (2023)

Hybrid recommendation system of intelligent captioning using deep learning networks
Tekijä: Wasi, Ahamed Al, et al.
Julkaistu: (2024)

Text classification using machine learning algorithms
Tekijä: Hasnat, Fahim, et al.
Julkaistu: (2018)

A hybrid rumor detection model derived from a comparative study of supervised approaches
Tekijä: Aothoi, Mehzabin Sadat, et al.
Julkaistu: (2023)

An integrated approach: fake review detection using convBERT-BiLSTM classification
Tekijä: Mahmud, Md. Anas, et al.
Julkaistu: (2024)

Human sentiment analysis using natural language processing
Tekijä: Shamya, Md. Shamiul Haque Khan, et al.
Julkaistu: (2024)

Analysis on the effects of wallstreetbets on the stock market
Tekijä: Hossain, Abir, et al.
Julkaistu: (2022)

Assistive Guideline of Categorization for Competitive Programming Problems
Tekijä: Dhrubo, Najmus Sakib, et al.
Julkaistu: (2021)

A machine learning approach to predict young voter enthusiasm based on non-political factors
Tekijä: Rahman, Md. Nowroz Junaed, et al.
Julkaistu: (2021)

A feature selection approach to determine obesity using machine learning method
Tekijä: Antor, Shahidul Alam, et al.
Julkaistu: (2021)

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
Tekijä: Alam, Auninda, et al.
Julkaistu: (2021)

Sentiment classification on Bengali food and restaurant reviews
Tekijä: Hossain, Abid, et al.
Julkaistu: (2024)

Novel approach to detect hate speech and profanity on online platforms
Tekijä: Pritha, Barha Meherun, et al.
Julkaistu: (2022)

A study on the efficacy of natural language generation techniques for similar writing personalities
Tekijä: Anwar, Ahmed, et al.
Julkaistu: (2024)

Comparing the performance of time series models for forecasting exchange rate
Tekijä: Newaz, M.K.
Julkaistu: (2010)

Microsoft Word 2010 step by step /
Tekijä: Cox, Joyce, 1946-
Julkaistu: (2011)

Mastering Word 2000 /
Tekijä: Mansfield, Ron
Julkaistu: (1999)

Estimating flood susceptibility of Bangladesh in the future year using machine learning
Tekijä: Alim, Sakib Bin, et al.
Julkaistu: (2021)

Predicting brain age from EEG signals using machine learning and neural network
Tekijä: Pratanu, Abul Mushfique Muslah, et al.
Julkaistu: (2023)

Human resource policies of Bay Agro Industries Limited
Tekijä: Khan, Nazray Morshed
Julkaistu: (2017)

Islamic Finance and Anti-Money Laundering and Combating the Financing of Terrorism (AML/CFT) /
Tekijä: Kyriakos-Saad, Nadim
Julkaistu: (2016)

Prediction of diabetes induced complications using different machine learning algorithms
Tekijä: Rahman, Tahsinur, et al.
Julkaistu: (2018)

Intrusion of Malware (DDoS) detection in IoT devices using Machine Learning on Cyberspace
Tekijä: Al Amin, Istiak, et al.
Julkaistu: (2022)