Recently, I had a chance to catch up with University of Indiana’s social mood researcher Huina Mao.
Mao and her colleague Dr. Johan Bollen (his audio interview is available here>>) spoke at the inaugural Socionomics Summit, about their landmark study “Twitter Mood Predicts the Stock Market.” This year, they’ll both return to report on their latest research (to attend the conference reserve your seat here>>).
Jill Noble: We are so glad to have you back for this year’s Summit. Last year the audience really enjoyed your presentation. Would you tell us about your experience?
Huina Mao: Thank you. I absolutely enjoyed the event in 2011 — it was a brand new experience for me. As an informatics student, it was my first time to come to this type of a financial conference.
I very much liked the presentations from Robert Prechter, John Casti and Ken Olson. Another important thing I gathered from the conference is (I still remember) at the end of his presentation, Robert Prechter introduced some other works from behavioral financial economics, so from there I came to know about Robert Schiller and other major scholars in [the field].
J.N. We’re glad to hear that! Please tell us about what you’ve been up to since then.
H.M. Over the past year, I have also attended two more academic conferences about behavioral finance. I just took my first course in behavioral finance, too.
Beforehand, I read several books on behavioral finance and traditional finance to understand the subject. I didn’t want to push myself to believe anything. As you know, with different schools of finance there are a lot of arguments, with a lot of division between sides. I didn’t want to identify with one particular side — I wanted to have an open mind and to learn the different approaches so that I can know more before I have my opinion.
When we started working on Twitter Mood Predicts the Stock Market, we didn’t know much about behavioral finance and socionomics. We didn’t know that there was already a lot of literature and existing theories that emphasized social mood in finance. We kind of accidentally began work on it, without knowing much about the theory itself.
All of this affected the work that I’m doing right now, inspiring me to investigate more about what we are measuring; whether it’s information, sentiment, or some of both. Basically, I wanted to figure out “What is behind Twitter mood?” This is what I will discuss in my presentation this year — my analysis underneath all of this.
One point that I got from the Summit last year was to start looking at longer term analysis. Before, we didn’t know whether our signals may have some long term trend information: In my current research we are looking at the long term effect of sentiment.
J.N. That’s great — we are all looking forward to learning more about your work. Is there anything in particular that you’re looking forward to about the upcoming Summit?
H.M. Last year’s Socionomics conference opened my eyes to things that I didn’t know before. I’m excited to hear more about the progress on your side and research updates from the Socionomics Institute. My expectation for this year’s Summit is to talk with more people to collect feedback from others about our work so that I can keep myself on the right track.
Last year I had a discussion with Dr. Ken Olson over lunch during the conference, and these outside discussions were also something I really liked about the Summit.
J.N. Thank you, Huina. We’re really looking forward to seeing you in April.
This year’s Socionomics Summit: New Initiatives in Social Mood Research and Application promises to be another wonderful opportunity to hear from and mingle with an impressive group of presenters and attendees.