Information Explosion Revisited

So the conversation has been brought back to the information explosion problem.  

I was talking to Stanley this morning before we headed to lunch, about the fact that there's just too much information on our screen everyday. All these years the "information explosion" problem has been discussed about over and over again, yet we still haven't got many good solutions to it. Well yes, of course there are some. Quora's good, and StackOverFlow is good - they help you find the answers in a Q&A fashion. Wikipedia is good because it gives you the "legit" introduction for things in a "official", or encyclopedic tone. People like these web services because they give us the answers rather than the links to potential results (like what search engines do), but unfortunately there're many more things we want to know that cannot be presented naturally in these forms. 

Why? I think there are two reasons for it. First, the questions are open questions that have no single, true answer, e.g. "Should we abandon nuclear power?", "Is Apple still gonna innovate after Steve Jobs?". Answers to these questions come with opinions and perspectives, which may sometimes even need to be involved with emotions. Second, a lot of the time what we are looking for are similar experiences or stories to our own scenarios, rather than definitive, yes-no answers. For example, "Should I take their offer and sell my startup now? Or should I keep trying and follow my passion?", "Should I send my kids to those private schools that are very visionary and experimental? Or should I stick to the traditional education system?" It is very hard when you're not sure what exact keywords to type into Google, and it's even harder when you're not sure if you'd necessarily agree with the value systems of the providers of what you've found.
 
What we're trying to do in StorySense Computing is to provide a way for people to communicate their thoughts and experiences in the form of stories, by helping them collect materials from the web without distracted by irrelevant search results, and organize these useful materials into meaningful threads to make their points. It's like wikipedia, where we provide editing tools for the editors and browsing tools for the readers, but the interface is a lot more visual and the search behavior is seamlessly integrated into the editors' storytelling behavior, that they can be encouraged to constantly focus on their points to make. We achieve this by displaying relevant keywords to users' input using a mindmap-like graph, so the users can focus on the associated keywords and the highly-relevant articles found. The produced stories can be exported as videos or javascript storyboards, and can be easily shared on social network platforms. The revenue comes from users who want to save their produced stories as private (like Github or Prezi's freemium model), and the first group of users would be people with strong opinions on the Internet that have strong passion to address certain topics by collecting and leveraging facts about public events.

Our philosophy is that, when people answer questions that have no definite answers, we engage in conversations. The person who answers the question may try to understand the counterpart's situated scenario first, and then provides her views by sharing her past experiences or others' stories she thinks are relevant. The cognitive process of describing these experiences are in fact a storytelling process, where the key element of stories - characters, events, time, location, objects, emotions - are composed to form higher-level concepts such as attitudes, standpoints, values, goals, lessons, etc. We exchange these higher-level concepts when the stories are told, and apply them into our own situations to decide what we answers want for ourselves. The goal of this tool is to simplify the storytelling process, making the produced stories visual and easy to consume, and democratize it so that more and more people can benefit from the sharers' valuable experiences. It may also track the editors' thinking trajectories, so that other people can benefit when thinking about the same question, which we think can save a huge amount of time previously wasted.