This is the strategic project of YouNet, aiming at providing a search engine which can retrieve appropriate social networks based on given keywords. In particular, we gradually focus on niche social networks, rather than general ones like Facebook, Twitter or Linkedin. Such a search engine would be useful for those who want to find communities of interest; for social network site owners who want to find similar sites or competitors of their sites and especially for marketers who want to locate suitable market domains for certain products.
Currently, version 1.6 of the search engine is avalaible at http://search.younetco.com/search. Apart from the basic functions provided, we also give users some featured information sucha as top 100 social networks in the world or the presently emerging social networks. Social networks are also categorized for browsing and indexing by interesterd users. All of those features are performed automatically using self-developed research tools of YouNet. More advanced search functions will be included to the system soon.
How to monetize the site contents is always a constant concern of social network owners. Affiliation program has been proved as an effective approach to achieve this goal. However, with the given huge amount of product data available today, how to deliver affiliated product advertisements into appropriate target users become increasingly important.
We deal with the problem by the concept of social sense. Based on some machine learning approaches, we can infer the key concepts mentioned in a social discussion. Therefore, the affiliated product advertisement can be selected wisely to be delivered to the corresponding users.
How to determine influential users in a social network is a hot topic attracting related research communities today. Some metrics have been suggested such as PROskore, Klout, Kred or PeerIndex, but so far no one proven completely dominant the others.
As a leading solutions provider for social networks, YouNet has certain advantages to analyze social structure and user relationships in a social network. Currently, we are developing our own approach for influential user determination in a social network, which will be integrated into our future products.
All of site owners of social networks always want to know what their users are talking about, especially the discussed trends emerging recently. This kind of information will certainly help the owners in many respects to promote their sites. YouNet is intensively conducting research on this issue, which can be considered as a combination of temporal analysis and content-based data analysis.
Sentiment classification means deciding whether a comment posted by a user is positive, negative or neutral. Keyword-based approach is usually applied in this situation. However, as some keywords are domain-independent, some of others are domain-dependent. It causes much difficulty when dealing with the cross-domain context, i.e. applying a model trained on a certain domain to another newly developed domain. YouNet is developing an innovative approach to deal with this problem.
—R&D Director, Quan Thanh Tho, Phd.—
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