• ANJU A
• SARAVANAN T.M

This project presents Forum Crawler Under Supervision (FoCUS), a supervised web-scale forum crawler. The goal of FoCUS is to crawl relevant forum content from the web with minimal overhead. Forum threads contain information content that is the target of forum crawlers. Although forums have different layouts or styles and are powered by different forum software packages, they always have similar implicit navigation paths connected by specific URL types to lead users from entry pages to thread pages. This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Facebook, Twitter, and YouTube present opportunities and challenges to study collective behavior on a large scale. This project aims to learn to predict collective behavior in social media. In addition, the project includes a new concept called sentiment analysis. Since many automated prediction methods exist for extracting patterns from sample cases, these patterns can be used to classify new cases. The proposed system contains the method to transform these cases into a standard model of features and classes. As a result, the behavior of individuals is collected through their posts in a forum and then they are classified as positive/negative posts. The cases are encoded in terms of features in some numerical form, requiring a transformation from text to numbers and assign the positive and negative values to each word to classify the word in the document.

Data mining, Sentiment Analysis, K Means clustering

"EFFECTIVE WEB CRAWLER MODEL FOR USER SENTIMENTAL ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.78-86, April-2019, Available :http://www.jetir.org/papers/JETIR1904109.pdf

"EFFECTIVE WEB CRAWLER MODEL FOR USER SENTIMENTAL ANALYSIS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp78-86, April-2019, Available at : http://www.jetir.org/papers/JETIR1904109.pdf