Gender-based feature analysis in campus-wide WLANs Export

@article{kumar:gender-poster, abstract = {Rapid WLAN deployment has led to various research challenges and scenarios. In this paper we come up with a technique to classify users into social groups and then use this information to investigate the usage behavior of these groups. Grouping of users can be done based on diverse parameters like gender, major or other interest groups. In this paper we show the general methodology used to accomplish WLAN user groupings with an example of grouping by gender in a major university campus. The usage patterns of Males and Females are contrasted based on this grouping. Possible applications of this work encompass user profiling; studying gender gaps in social sciences; announcement/advertisement customization to target groups.}, address = {New York, NY, USA}, author = {Kumar, Udayan and Yadav, Nikhil and Helmy, Ahmed}, citeulike-article-id = {5313520}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1374525}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1374512.1374525}, doi = {10.1145/1374512.1374525}, issn = {1559-1662}, journal = {ACM SIGMOBILE Mobile Computing and Communications Review}, keywords = {analysis, campus, crawdad, dartmouth\_campus, wlan}, month = {January}, number = {1}, pages = {40--42}, posted-at = {2009-07-31 21:28:02}, priority = {2}, publisher = {ACM}, title = {Gender-based feature analysis in campus-wide {WLANs}}, url = {http://dx.doi.org/10.1145/1374512.1374525}, volume = {12}, year = {2008} }

TY - JOUR ID - kumar:gender-poster L3 - citeulike-article-id:5313520 N2 - Rapid WLAN deployment has led to various research challenges and scenarios. In this paper we come up with a technique to classify users into social groups and then use this information to investigate the usage behavior of these groups. Grouping of users can be done based on diverse parameters like gender, major or other interest groups. In this paper we show the general methodology used to accomplish WLAN user groupings with an example of grouping by gender in a major university campus. The usage patterns of Males and Females are contrasted based on this grouping. Possible applications of this work encompass user profiling; studying gender gaps in social sciences; announcement/advertisement customization to target groups. IS - 1 JF - ACM SIGMOBILE Mobile Computing and Communications Review SN - 1559-1662 AD - New York, NY, USA EP - 42 TI - Gender-based feature analysis in campus-wide {WLANs} PB - ACM VL - 12 SP - 40 KW - analysis KW - campus KW - crawdad KW - dartmouth_campus KW - wlan AU - Kumar, Udayan AU - Yadav, Nikhil AU - Helmy, Ahmed PY - 2008/January// UR - http://dx.doi.org/10.1145/1374512.1374525 ER -