Opinion Mining For Comment Sentiment Analysis

Download Document/Synopsis
Here we propose an advanced Comment Sentiment Analysis system that detects hidden sentiments in comments and rates the post accordingly. The system uses opinion mining methodology in order to achieve desired functionality. Opinion Mining for Comment Sentiment Analysis is a web application which gives review of the topic that is posted by the user. The System takes comments of various users, based on the opinion, system will specify whether the posted topic is good, bad, or worst. We use a database of sentiment based keywords along with positivity or negativity weight in database and then based on these sentiment keywords mined in user comment is ranked. Once the user logins to the system, user can view his own status as well as he can view the topics posted by the admin. When the user clicks on a particular topic user can give his own comment about the topic. System will use database and will match the comment with the keywords in database and will rank the topic. User can edit his own profile and can change his profile picture. The role of the admin is to add post and adds keywords in database. This application can be used by users who like to post view about some events that is already held, or can post about the events that is going to be held. This application also works as an advertisement which makes many people aware about the topic posted. This system is also useful for the user’s who need review about their new idea. This system is also useful for the user’s who need review about any particular event that is posted.



Advantages
  • User can easily share his view about the topic.
  • People can easily decide whether the posted topic is good or bad by using this application.
  • This application is more useful for the users who love to comment.
  • Since system ranks the topic based on the keywords in database so the result is appropriate.
Disadvantages
  • System will match the opinion with those keywords which are in database rest of the words are ignored by the system.

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