Search engine user behaviour How can users be…

Search engine user behaviour: How can users be guided to quality content? :

“The typical behaviour of the Web search engine user is widely known: a user only types in one or a few keywords and expects the search engine to produce relevant results in an instant. Search engines not only adapt to this behaviour. On the contrary, they are often faced with criticism that they themselves created this kind of behaviour. As search engines are trendsetters for the whole information world, it is important to know how they cope with their users’ behaviour. Recent developments show that search engines try to integrate results from different collections into their results lists and to guide their users to the right results. These results should not only be relevant in general, but also be pertinent in the sense of being relevant to the user in his current situation and in accordance to his background. The article focuses on the problems of guiding the user from his initial query to these results. It shows how the general users are searching and how the intents behind their queries can be used to deliver the right results. It will be shown that search engines try to give some good results for everyone instead of focusing on complete result sets for a specific user type. If the user wishes, he can follow the paths laid out by the engines to narrow the results to a result set suitable to him.”


Academic Search Engine Spam and Google Scholar’s Resilience Against it

In a previous paper we provided guidelines for scholars on optimizing research articles for academic search engines such as Google Scholar. Feedback in the academic community to these guidelines was diverse.

Some were concerned researchers could use our guidelines to manipulate rankings of scientific articles and promote what we call ‘academic search engine spam’. To find out whether these concerns are justified, we conducted several tests on Google Scholar.

The results show that academic search engine spam is indeed—and with little effort—possible: We increased rankings of academic articles on Google Scholar by manipulating their citation counts; Google Scholar indexed invisible text we added to some articles, making papers appear for keyword searches the articles were not relevant for; Google Scholar indexed some nonsensical articles we randomly created with the paper generator SciGen; and Google Scholar linked to manipulated versions of research papers that contained a Viagra advertisement.

At the end of this paper, we discuss whether academic search engine spam could become a serious threat to Web-based academic search engines.

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