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Ads in Facebook.

Paravastu Pattarabhiran, Lavanya.

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Ads in Facebook.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Ads in Facebook./
作者:	Paravastu Pattarabhiran, Lavanya.
面頁冊數:	65 p.
附註:	Source: Masters Abstracts International, Volume: 51-02.
Contained By:	Masters Abstracts International51-02(E).
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1520038
ISBN:	9781267672919

Ads in Facebook.
Paravastu Pattarabhiran, Lavanya.

Ads in Facebook. - 65 p.

Source: Masters Abstracts International, Volume: 51-02.

Thesis (M.S.)--Rutgers The State University of New Jersey - New Brunswick, 2012.

Understanding the relevancy of user-targeted ads on social networking websites requires the information about the heterogeneous user data and the corresponding ads that are targeted towards the user. This can be accomplished by performing a large scale collection of ads seen by users online on various social networking sites. For the purpose of this research, Facebook was considered as the social networking website. Since using real user profiles may involve privacy issues, dummy profiles were created and the targeted ads were analyzed. Moreover, in order to limit the amount of data being collected and analyzed, the study targeted Facebook ads from a region, India. An automated script in java and selenium was also developed to collect the ads that were targeted at the dummy profiles created. The data collected was analyzed using General Linear Modeling to understand the dependency between category of advertisement shown to a user and profile characteristics like age, gender and location.

ISBN: 9781267672919Subjects--Topical Terms:

626642
Computer Science.

Ads in Facebook.
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520 $a Understanding the relevancy of user-targeted ads on social networking websites requires the information about the heterogeneous user data and the corresponding ads that are targeted towards the user. This can be accomplished by performing a large scale collection of ads seen by users online on various social networking sites. For the purpose of this research, Facebook was considered as the social networking website. Since using real user profiles may involve privacy issues, dummy profiles were created and the targeted ads were analyzed. Moreover, in order to limit the amount of data being collected and analyzed, the study targeted Facebook ads from a region, India. An automated script in java and selenium was also developed to collect the ads that were targeted at the dummy profiles created. The data collected was analyzed using General Linear Modeling to understand the dependency between category of advertisement shown to a user and profile characteristics like age, gender and location.
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