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With the increasing popularity of social means to satisfy information needsusing Social Media (e.g., Social Media Question Asking, SMQA) or SocialInformation Retrieval approaches, this paper tries to identify types ofinformation needs which are inherently social and therefore better suited forthose techniques. We describe an experiment where prominent websites fromvarious content categories are used to represent their respective content areaand allow to correlate attributes of the content areas. The underlyingassumption is that successful websites for focused content areas perfectlyalign with the information seekers' requirements when satisfying informationneeds in the respective content areas. Based on a manually collected dataset ofURLs from websites covering a broad range of topics taken from Alexa(http://www.alexa.com} (retrieved 2015-11-04)) (a company that publishesstatistics about web traffic), a crowdsourcing approach is employed to rate theinformation needs that could get solved by the respective URLs according toseveral dimensions (incl. sociality and mobility) to investigate possiblecorrelations with other attributes. Our results suggest that information needswhich do not require a certain formal expertise play an important role insocial information retrieval and that some content areas are better suited forsocial information retrieval (e.g., Factual Knowledge & News, Games, Lifestyle)than others (e.g., Health & Lifestyle).

Estimating the Dissemination of Social and Mobile Search in Categories of Information Needs Using Websites as Proxies