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In scientific field what we present to the general public is not always the whole truth. As scientific theories become obsolete by new discoveries so frequently, reports done based on those topics get obsolete, and may misinterpret sometimes.

We are solving this problem by giving a report 'Life', a way to grow and evolve itself on its own. By just integrating the 'Social Stream' with the main report. This ‘social stream’ is basically what people are talking about on a particular topic throughout the social media like Twitter, Facebook, Pinterest and all other publicly available online streams.


So the idea is to turn a static science report/post into a social stream. We still use the ancient format of presenting reports like main report + related posts + comments. But the era of social media have changed everything. Now a days people don't just comment in any blog. They share the post and give their opinion to their friends, rather commenting in some unknown world. So to collect what they are saying, how the overall story get evolved we need to crawl through this publicly available data stream. Yes, now-a-days we surf through this data by Big data and Artificial Intelligence. But we just use it for our own reporting. This huge amount of information stream got squeezed in a newsroom, funneled to the next fabricated report, and a brutal murder of a story happens in our own newsroom.

This is not the end. Now assume you, me and everyone in the world live in same kind of houses, same look alike, same setup, same furniture. How ridiculous is that! Yes, we are doing this ridiculous thing to our readers for last couple of decades. Everyone reading same story although they have whole lot of different perspectives. By integrating social stream we are not just giving it life, we can make it more personal and familiar even a friend to the reader. How?

The idea is simple. Personalized Social Stream. Showing the stream of their social media friends, the stream based on the topics they liked in social media, or even by their demographics or using cookies and browser stories, like what google and other advertising agencies do to show their advertisements.

To integrate data from Facebook, Twitter, Pinterest, Google plus we are using their public API. On the other hand web scraper like Import IO, Kimono, Scrapy, Nutch can scrape publicly available data from websites. This online data streams are than filtered by demographic which are focused on race, economic status, sex, age, level of education, income level and employment or they can be psychographic focused which are based on the consumer’s values, personality, attitudes, opinions, lifestyles and interests. They can also be behavioral variables, such as browser history, purchase history, and other recent activity. 3rd party tools like Clicksor can do this targeting job. Later we can use Artificial Intelligence like IBM Watson to learn more about the behavior of a reader and automate the whole process.