Deriving sentiment and attributes from web logs and development of hierarchical value map of derived attributes

Abstract

The objective of the project is to1. Derive Sentiment and Attribute towards a product/company/brand by mining Web logs, also known as Blogs.2. Derive effect of Corporate Communication on the sentiments expressed through Blogs.3. Derive Value Map on the attributes of the selected product. Motivation: The sheer numbers of Blogs have grown considerably in last few years. As of November 2006,Blogs search engine Technorati was tracking nearly 60 million Blogs. With the explosive growth of data generated by Bloggers, Blog mining seems to have become more important than ever. The consumers expressing their feeling, emotions on these Blogs the motivation for the project was how to does the sentiment expressed in these Blogs can help market researchers in coming up with new strategy in understanding the ever evasive consumer mind. The major challenges faced today are: How technology can help in Blog mining as it is humanly impossible to read all the Blogs? How to structure the data for quantitative analysis for the expression language used in the Blogs? Can Blogs provide insights into the core decision making values of a consumer? AOL is the world's leading interactive services provider. It has been in the business of providing internet service over the last two decades. However, with the advent of Wi-Fi and other broadband sources, the focus of the AOL has changed from a service providing business to advertisement revenue based. While most of the members are opting to take the Free AOL approach, AOL is trying to understand how it can differentiate itself from similar companies like Yahoo!, MSN etc. We believe that blogs will give us an insight into understanding exactly this.