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Social ads are increasingly assuming mainstream status, as brands focus on devising newer ways to engage user attention. While traditional advertisers focus on targeting users with contextual ads wherein ads are served on the basis of content, in social advertising factors such as peer and social influences as well as recommendations are taken into consideration for targeting users. Rapid increase in social media activities in the recent years has driven advertisers to take up social ads.

Marketers will spend over $350 billion advertising on the web this year "betting" that they will reach the intended market of buyers. Advertisers create slick campaigns "betting" that they will get the markets attention to their offering. Betting is a game, sometimes you win and most of the time you lose.

What do Color, Quora, Hunch, Blippy, and StockTwits have in common? They are examples of companies that generate value for their users by leveraging the concept of the Interest Graph. The list also features some of the most promising startups right now, having raised close to $100 million in venture funding. Pure coincidence?

EBay said it will use Hunch's "taste graph" technology to provide its users with non-obvious recommendations for items based on their unique tastes. The company said it will also apply Hunch's technology to other areas such as search, advertising and marketing, in order to better surface product information based on its customers' tastes.

Web search engines have become indispensable tools for finding information online effectively. As the range of information, context and users of Internet searches has grown, the relationship between the search query, search interest and user has become more tenuous. Not all users are seeking the same information, even if they use the same query term. Thus, the quality of search results has, at least potentially, been decreasing. Search engines have begun to respond to this problem by trying to personalise search in order to deliver more relevant results to the users. A query is now evaluated in the context of a user's search history and other data compiled into a personal profile and associated with statistical groups. This, at least, is the promise stated by the search engines themselves. This paper tries to assess the current reality of the personalisation of search results. We analyse the mechanisms of personalisation in the case of Google web search by empirically testing three commonly held assumptions about what personalisation does. To do this, we developed new digital methods which are explained here. The findings suggest that Google personal search does not fully provide the much-touted benefits for its search users. More likely, it seems to serve the interest of advertisers in providing more relevant audiences to them.

We feel the need to belong, to form a part of a group who make us feel wanted, and loved and understood. And what better place to do that than the Internet? We're not suggesting you stop going out more often, but there are increasing signs of "like-minded" individuals e-huddling together and carrying out activities which are of common interest, and this is where niche social networking steps in.  By targeting a specific audience, a niche social networking site is able to create an automatic bond between people

The growing company "offers an advanced semantic page-level analysis that surfaces reader emotions, behaviors, motivations and intentions in order to match ads with similar emotional appeal, without using tracking cookies.