It is two months now of reading papers since I started my PhD program. Enough time to think about possible research topics. I am more and more interested in search, social networks in general and social news streams in particular. It is obvious that it is becoming more and more important to aggregate news around a users interests and social circle and display them to the user in an efficient manner. Facebook and Twitter are doing this in an obvious way but also Google, Google News and a lot of other sites have similar products.

To much information in one’s social environment

In order to create a news stream there is the possibility to just show the most recent information to the user (as Twitter is doing it). Due to the huge amount of information created, one wants to filter the results in order to gain a higher user experience. Facebook first started to filter the news stream on their site which lead to the widely spread discussion about their ironically called EdgeRank algorithm. Many users seem to be unhappy with the user experience of Facebook’s Top News.
Also for some information such as the existence of an event in future it might not be the best moment to display the information as soon as it becomes available.

Interesting research hook points and difficulties

I observed these trends and realized that this problem can be seen as a special case of search or more general recommendation engines in information retrieval. We want to obtain the most relevant information updates around a certain time window for every specific user.
This problem seems to me algorithmically much harder than web search where the results don’t have this time component and for a long time also haven’t been personalized to the user’s interest. The time component makes it hard to decide the question for relevance. The information is new and you don’t have any votes or indicators of relevance. Consider a news source or person in someone’s environment that wasn’t important before. All of a sudden this person could provide a highly relevant and useful information to the user.

My goal and roadmap

Fortunately in the past I have created metalcon.de together with several friends. Metalcon is a social network for heavy metal fans. On metalcon users can access information (cd releases, upcoming concerts, discussions, news, reviews,…) about their favorite music bands, concerts and venues in their region and updates from their friends. These information can perfectly be displayed in a social news stream. On the other hand metalcon users share information about their taste of music, the venues they go to and the people they are friend with.
This means that I have a perfect sandbox to develop and test (with real users) some smart social news algorithms that are supposed to aggregate and filter the most relevant news to our users based on their interests.
Furthermore regional information and information about music are available as linked open data. So the news stream can easily be enriched with semantic components.

Since I am about to redesign (a lot of work) metalcon for the purpose of research and I am about to go into this direction for my PhD thesis I would be very happy to receive some feedback and thoughts about my suggestions of my future research topic. You can leave a comment or contact me.

Thanks you!

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4 Comments on Social news streams – a possible PhD research topic?

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