Leveraging the Power of Google to Perform Research

As a writer, there is undoubtedly no better tool for researching than Google. This article focuses on how to use Google to find analyst research, important data and other factoids that will round out the quality of your white papers.

Stelzner, Michael A. WhitePaperSource (2006). Articles>Writing>Research>Search

Seek and Ye Shall Find

It's the information age, you know... it has been for a while. You hear people say that you can find anything on the Internet. What they don't tell you though, is how. Sure, there are search engines and there are SEARCH engines, but nobody tells you how to use them properly. Well, this is about how to make the most of search engines. While this article is written with a focus on Google (www.google.com), the principles can be applied to other search engines as well.

Alfred, P.M. Indus (2003). Articles>Research>Search

The Winning Mindset: Effective Competitive Intelligence Research on the Internet    

Suggests that search engines are useful but limited in their application for competitive intelligence searching on the internet, and highlights the importance and effectiveness not just of structured searching but also of creativity. Explains some of the technical limitations of internet searching and suggests conditions in which a competitive intelligence search may be made more effective, pointing out that the value an information professional adds is in having some idea in advance of what they are likely to find. Gives details of what search engines will and will not retrieve, and illustrates how search strategies can be improved through use of the available filtering syntax. Suggests that using Boolean logical operators and other features directly in the search box is likely to produce better results than simply relying on the search engine's advanced search feature. Concludes by re-emphasizing the need for a creative mindset, building on some structure.

Kendrick, Terry. Business Information Review (2007). Articles>Research>Online>Search

Why We Search: Visualizing and Predicting User Behavior  

The aggregation and comparison of behavioral patterns on the WWW represent a tremendous opportunity for understanding past behaviors and predicting future behaviors. In this paper, we take a first step at achieving this goal. We present a large scale study correlating the behaviors of Internet users on multiple systems ranging in size from 27 million queries to 14 million blog posts to 20,000 news articles. We formalize a model for events in these time-varying datasets and study their correlation. We have created an interface for analyzing the datasets, which includes a novel visual artifact, the DTWRadar, for summarizing differences between time series. Using our tool we identify a number of behavioral properties that allow us to understand the predictive power of patterns of use.

Adar, Eytan, Daniel S. Weld, Brian N. Bershad and Steven D. Gribble. WWW 2007 (2007). Articles>Web Design>Search>Research