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Browsing MS DEPARTMENT OF INFORMATION SYSTEM by Author "Adil Rehman"

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    Se-Bert Emotion Based Sentiment Analysis
    (UMT, Lahore, 2022) Adil Rehman
    Now a days, a lot of data is produced due to popularity of social network sites, i.e., Twitter, Facebook and Instagram. Due to the brief and straightforward terms used in microblogging, millions of people share their opinions every day. I’ll talk about a technique for takeout sentiment from Twitter, a well-known platform for microblogging where users can express their opinions on virtually everything. In this paper, I used different models by using two sentiment-based datasets. Twitter dataset of sentiments and emotional sentiment dataset. Firstly, I extracted the sentiments and text from twitter dataset, after the extraction and preprocessing used three different models such as RNN and BiLSTM and pre-trained BERT model. Secondly, in the relationship between user’s sentiment, I compare different models RNN and BiLSTM and BERT to determine the good and accurate result. First dataset includes two categories that are “positive” and “negative” and Second dataset belongs to six categories of feelings such as “joy”,” sadness”, “love”, “fear”,” anger”,” surprise” etc. BERT pretrained Model mainly used to get relation between previous and next sentence but there I used for emotional sentiment analysis, so there I proposed a model named Se-Bert for emotional sentiment analysis which is described after pretrained model BERT (bidirectional encoder representations from transformers) implementation. I proposed our model in experiments that I found different results in tweet sentiments had a significant impact on fetching or knowing about user’s behavior. The experiments demonstrate that the Se-Bert model put out in this paper is capable of accuracy levels of 97.29% and 86.77% in two different datasets of tweets sentiments and emotional sentiments simultaneously, the result that Se-Bert, which I developed, outperforms both RNN and BiLSTM techniques.