Identifying Click Fraud

MERRICK, NY–(Marketwire – April 15, 2016) – New research published in the Conference Proceedings of the Northeast Decision Science Institute, proposed and analyzed a unique method for attempting to identify click fraud traffic to websites. The research conducted by Nooshin Nejati and Dr. Alexander Pelaez, proposed examining immediate behaviors of activity, i.e. clicks and time between clicks, to identify “dark traffic”. According to the New York Times (Dec 9, 2014, L. Kaufman), click fraud cost companies over $6 Billion dollars annually (2015 estimate). “Click Fraud detection in not only important for advertising base businesses, but is also a key factor for any other technology related business to eliminate fraud activities before further data analysis influences business decisions prematurely”, said Ms. Nejati.

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Dispelling illusions using Visualizations

Visualizations are a great data exploration technique. Our human minds are better able to understand and retain visuals than scripts or text. Visualizations, apart from giving us a good general overview of the data, entail us with an intuitive understanding of the distribution of the dataset and its trends.
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Tracing Search Behavior using Social Network Analysis

Introduction

The aim of this paper is to study the search behavior of users, based on their Google search query terms, and to find similarities between search behaviors of a pool of users. We want to identify the types of searches that are central to other searches. These searches would ideally lead to searches of other kinds, and it would be conducive to invest in Google ads for searches of this type. Continue reading Tracing Search Behavior using Social Network Analysis