Influence of social media and intelligent recommendation systems on research and expert finding

Infographic on how Social Media are being used...

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Social media play an ever increasing role in the kind of information we get to see and especially how (fast). More than ever, any individual gets the opportunity to consume (after paying a fee) scientifific articles that they desire. Besides that it’s possible via news groups, forums, faq-sites, blogs and social networks to contribute ideas as a new article or directly as a quick tought directly to followers or subscribers. People no longer publish only in their free time or as a hobby. Professionals, experts, researchers and educators are increasingly using social media. Defining an expert or shaping a research project evolves enormously under influence of new technology as intelligent recommendation systems  who massively starting to adopt social media in their algorithms.

Every expert has developed his own personal way practicing and performing. Social media offer a way for experts to differentiate them even more. Rather than following one influencive professor or teacher in a niche group, they have the chance to quickly discover different methods to improve very specific aspect of their research and methodology. Intelligent recommendation systems will behave as the guide for every expert and researcher along their path, just as the old-school teacher did before the arrival of complex information systems and social media. Every consumer and producer of information learns to quickly pick-up the right puzzlepieces and to process them to a deliverable (such as a report, article, analysis, synhthesis…). Properly implemented information systems who incorporate feedback of their users can improve their service even faster as intelligent filtering algorithms are more and more focussed on collaborative input.

It  is important for any expert or researcher to keep practicing their information processing skills. It is a cumulative effect, the so-called “Power-Law“. Experiments have shown that there is a neuroplasticity effect on the brain by the environment. A high-tech environment with lots of valuable inputs thus should have a more effective impact than an environment in which expert has to dismiss to much stuff instead of being able to focus on the right piece of information at the right time. The fast technology shift is so fast that basic reading, analysis and synthesis for reading and selecting texts are a good base, but not enough to be able to keep track of the ever increasing offer on information. Instead of really having to specialize in one certain area and having to read, let’s say all the material in that area, the task of an expert researcher now is more and more in having their ways of dealing with the diversity of methods to access the right piece of information and judging whether it’s a suitable piece or not. This kind of expertis is very time and location specific. Intelligent recommendation systems allow experts and researcher to define and keep track of the pieces which they have the most affinity with at a certain point in time from an immense pool of pieces. They are no longer limited to the resources in their local and often niche-environment. It is therefore less and less opportune for companies or institutions to invest in the education of very specific experts as it’s very unlikely that they will stay long enough to achieve that goal. Experts will temporarely gain expertise for a specific research project driven by powerful affinity and supported by an immense community of people interested in the same topic. The task of the experts is to bring to pieces together and achieve their research goals, same as before the technology and social media evolution, but much faster. Think of it as playing chess where at every move you can ask feedback from the community, instead of having to think of the best solution you have a set of possible solutions and you have to learn and judge which suggested move give you most chance to success.

So expert training to develop the necessary plasticity still has an important role, but the focus is different. It’s far more important to quickly judge the value of suggested or found pieces, would it be by a search engine, recommendation system or another expert. This requires an even higher pragmatic skill of every expert than ever before. The better you are able to formulate your problem for the community, the better results you can achieve. Depending on your level or estimated difficulty of the problem, intelligent recommendation systems can help researchers with formulating and being aware of the research goal at a certain moment. An amateur musician who has a great affinity with a certain piece of music can still have its own very important and more valuable interpretation to some other listener than a professional musician. It is only hard for the listener to find that one amateur (of thousands) that has the most amazing interpretation and performance (for him) compared to the ease of finding the professional performance.

The arrival of social media and intelligent recommendation systems has made it possible that both young and experienced researchers can focus more on specific aspects they have great affinity with, both as consumers (listeners) or producers (performers). They all can deliver a valuable expertise to someone else. The new technology brings all those people closer together than ever before. The possibility to follow our affinities as they evolve through our lives is very important as it keeps researchers motivated and thus the quality of produced content increases, which helps to ignite interested readers and so on. The exchange of experiences and possibility to improve skills is guaranteed by the giant network of information: Internet. The Internet is no longer a huge static source of information, like a digital library. The Internet is a way to be able to focus more on the own temporary interests more intensively by combining puzzlepieces from various sources to new information that can be reused by others. Intelligent recommendation systems make this information more accessible and bring researchers and experts in touch with each other.

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About laurensdv
Computer Science Student, interested in creating more innovating user experiences for information access. Fond of travelling around Europe!

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