Real insighth: complete opinion analysis system
| dc.contributor.author | Khan, Tabrez | |
| dc.contributor.author | Sarole, Arafat Mohd Wasim (17CO41) | |
| dc.contributor.author | Khan, Haris Shafiqurrehman (16CO27) | |
| dc.contributor.author | Ansari, Hamdan Shakir (17CO25) | |
| dc.contributor.author | Lakdawal, Aryan Sajid (17CO33) | |
| dc.date.accessioned | 2021-12-13T05:13:53Z | |
| dc.date.available | 2021-12-13T05:13:53Z | |
| dc.date.issued | 2021-05 | |
| dc.description.abstract | Real Insights: A Complete Opinion Analysis System The purpose of this project is to make the process of taking feedback from the audience in events, lectures, seminars regarding the understanding of the event. As this is the online era, where everything is online we need to develop a system which is very useful to maintain the feedback by the administrator. With this the organization can access the feedback reports in a faster way and without any loss of data. As of now this task is usually done using pen and paper. This has many drawbacks and evaluating this handwritten form is a difficult process. Along with Sentiment analysis we can easily automate the procedure of analysing feedback of every event of an organization. Sentiment analysis or opinion mining is the computational study of people’s opinions, sentiments, attitudes, and emotions expressed in written language. It is one of the most active research areas in natural language processing and text mining in recent years. Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of the people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on the customer’s ease, making choices with regards to online shopping, choosing events, products, entities. This paper aims at analyzing a solution for feedback systems by performing sentiment analysis at a fine-grained level, namely the sentence level in which polarity of the sentence can be given by three categories as positive, negative and neutral. Keywords: Feedback, Sentiment, Text mining, ML, Fine grained, Tedious, Algorithm, NLP, Data mining, Analysis, API, Dataset, Web Module, Framework, Authentication, Sentiment, Digital Customers, Routing, User Interface, JSON, Testing, MVC | en_US |
| dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3779 | |
| dc.language.iso | en | en_US |
| dc.publisher | AIKTC | en_US |
| dc.subject | Project Report - CO | en_US |
| dc.title | Real insighth: complete opinion analysis system | en_US |
| dc.type | Project Report | en_US |