Browsing by Subject "Sentiment analysis"

Now showing items 1-20 of 26

    • An advanced hospital rating system using machine learning and natural language processing 

      Tamjid, Ali Asgar; Galpo, Gaurab Paul; Urmi, Khadija Begum; Chitto, Fatema Sadeque; Annafi, Sadia (Brac University, 2023-05)
      Bangladesh is the host of 255 public and 4,452 private hospitals. Unfortunately, there is no reliable metric or resource available online to determine which hospital is better. Patients and their peers often find it ...

    • Analysis on the effects of wallstreetbets on the stock market 

      Hossain, Abir; Sarker, Zahid; Radib, Md Sadman; Taher, Sayed Bin; Samrat, Syed Mohebbullah (Brac University, 2022-01)
      In January of 2021, the stocks of various companies, i.e. Gamestop, AMC etc. had a huge surge in price. The incident was attributed to redditors of the subreddit called r/wallstreetbets making a massively coordinated ...

    • Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis 

      Shourin, Bushra; Shawgat, Kazi Sayef; Chowdhury, Serajur Reza (BRAC University, 2018-04)
      In this modern age where providing and consuming services through online exchange has become a daily chore, everyone loves to participate and give opinions about the services he or she consumes. Nowadays this participation ...

    • Aspect-based sentiment analysis using SemEval and Amazon datasets 

      Hasib, Tamanna; Rahin, Saima Ahmed (BRAC University, 2017)
      Sentiment analysis has become one of the most important tools in natural language processing, since it opens many possibilities to understand people’s opinions on different topics. Aspect-based sentiment analysis aims to ...

    • A deep learning approach to integrate human-level understanding in a Chatbot 

      Al Mamun, Amirul Islam; Abedin, Afia Fairoose; Nowrin, Rownak Jahn (2021-01)
      AI-powered computers like chatbots have taken over the market today to reduce human workload. Unlike humans, chatbots reply immediately, are available 24/7 and can assist several people at the same time. Due to the ...

    • A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations 

      Maliha, Miftahul Zannat; Trisha, Ananya Subhra; Tamzid Khan, Abu Mauze; Das, Prasoon; Shakil, Shuhanur Rahman (Brac University, 2023-01)
      For the technological shift, advancing epoch towards cryptocurrency intensified the impactful method. Metaverse can originate the base operation into a diversified level. The extension of digital marketing contributes ...

    • Detecting sarcasm in Bengali comments using NLP 

      Chowdhury, Md. Jamiur Rahman (Brac University, 2023-01)
      Natural Language Processing (NLP) is a subset of Machine Learning which resides at the intersection of Linguistics and Computer Science. It deals with the capability of computers to learn and work with human languages. ...

    • An effective machine learning approach for sentiment analysis of restaurant reviews 

      Karim, Rabita (BARC University, 2016-08)
      Sentiment analysis or opinion analysis is creating a vast area of research in this modern era of social media. Various blogs and Social Medias (Facebook, twitter, Instagram) are the most popular platform for the users or ...

    • Embedded system based bangla intelligent social virtual robot with sentiment analysis 

      Hossain, Md. Ishan Arefin; Hossain, Ismail; Hossain, Md. Yousuf; Banik, Mridul (BRAC University, 2018-04)
      Bangla is the mother tongue of millions of people all over the world. Despite of being a very popular language, any social virtual robot that can intelligently communicate in Bangla is a fairytale till now. One of the main ...

    • Feature based mobile phone rating using sentiment analysis and machine learning approaches 

      Kafi, Abdullahil; Alam, Md. Shaikh Ashikul; Hossain, Sayeed Bin; Awal, Siam Bin (2018)
      This project proposes a model of sentiment analysis of different features of different company’s mobile sets and rating them overall. Customers before buying a phone check reviews to get a better understanding of the device ...

    • Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model 

      Ghose, Swattic; Bin Khaled, Faiyaz; Rafin, Nafiz Imtiaz; Jawwad, Rubaiyet Hossain; Bin Yahiya, Yamin (Brac University, 2023-01)
      The decentralized cryptocurrency has created many opportunities for secure and safe financial transactions with a bright prospect. The cryptocurrency market rapidly expands, leading to erratic price movements due to ...

    • A machine learning approach to predict movie box-office success 

      Quader, Nahid; Gani, MD. Osman (BRAC University, 2017)
      Making a prediction of society’s reaction to a new product in the sense of popularity and adaption rate has become an emerging field of data analysis. The motion picture industry is a multi-billion dollar business. And ...

    • Market demand analysis using NLP in Bangla language 

      Hossain, Md Sabbir; Nayla, Nishat (Brac University, 2021-09)
      Product market demand analysis plays a significant role for originating business strategies due to its noticeable impact on the competitive business field. Furthermore, there are roughly 228 million native Bengali speakers, ...

    • Performing sentiment analysis in Bangla microblog posts 

      Chowdhury, Shaika; Chowdhury, Wasifa (© 2014 IEEE Computer Society, 2014)
      Much of the research work on sentiment analysis has been carried out in the English language, but work in Bangla is limited to only news corpus and blogs. Microblogging sites are becoming a valuable source for publishing ...

    • Predicting stock market movement using sentiment analysis of twitter feed 

      Chakraborty, Pranjal; Rony, Rashad Al Hasan; Pria, Ummay Sani (BRAC University, 4/16/2017)
      Collecting opinions of mass people through the social networking sites has become easy and handy now-a-days. These opinions show the sentimental state of a large number of people, which, according to behavioral economics, ...

    • Predicting stock market trend from twitter feed and building a framework for Bangladesh 

      Karim, Shabab; Abdullah, Tahmid; Tayaba, Umme (BRAC University, 2018-04)
      Social media has become an integral part in our day to day lives. What we share in these media are what we believe in and give others a window of opportunity to predict what is going on in our mind or how our actions ...

    • Product rating generation based on public opinion using sentiment analysis 

      Rabbi, Reshan Ahmed; Khan, Md. Walid Amin; Shaown, Md.; Alam, Md. Shajidul (BRAC University, 12/24/2017)
      In modern days, people tend to check reviews and opinions on a product before buying. The main goal of our system is according to the public opinion of a product, give a rating to the product on a scale of 0 to 10. Also, ...

    • Sentiment analysis for Bengali newspaper headlines 

      Hossain, Mohammad Samman; Jui, Israt Jahan; Suzana, Afia Zahin (BRAC University, 2017)
      In this project, we propose a system that assigns scores indicating positive or negative to newspaper headlines. Many works have been done on sentiment analysis, document clustering for newspaper headlines in English. We ...

    • Sentiment analysis in Bengali Text using NLP 

      Sarkar, Ankon; Sourav, Aishwarja Paul; Ahmed, Rezvi (Brac University, 2023-01)
      Natural Language Processing, a branch of AI, teaches computers to understand speech and text in multiple languages. Machine learning or deep learning techniques can be used to develop rule-based models of human-spoken ...

    • Sentiment analysis on Bangladesh airlines review data using machine learning 

      Hasib, Khan Md. (Brac University, 2022-02)
      A common means of transportation in our everyday lives is air travel. As a result, it's no surprise that more and more customers are posting their airline reviews online. However, in the age of machine learning, it would ...