Good morning I'm Rob Feenstra, professor of economics and also holder of
the C Brian Cameron Distinguished Chair in International Economics here at UC
Davis. I'm also Associate Dean of Academic Affairs in the Division of
Social Sciences and Director of the Center for International Data. It's my
pleasure to welcome you to the Institute for Social Sciences' spring conference,
"Recomputing Social Sciences: What Have We Learned Over a Decade?" At its yearly
conferences the Institute focuses on discussing and illuminating big
important questions facing social scienctists today. Just over a year ago ISS
hosted "Making Social Science Transparent", a conference that brought together
research from a diverse range of disciplines to confront the so-called
replication crisis. That crisis has not yet been averted. P-hacking remains a
significant threat to the credibility of social science. Indeed the American
Statistical Association declared just last year that while the p-value can be
a useful statistical measure it is commonly misused and misrepresented.
Compared with progress made in other sciences the social sciences frankly lag
behind in their ability to produce credible and replicable results. This is
especially problematic in the field of social psychology but economics is
hardly immune from this worry . At the same time this is a moment of
unprecedented opportunity. The digital footprint is transforming the social sciences from notoriously
data poor to abundantly data rich. This is certainly true in my own field of
international trade which was almost exclusively theoretical when I took it
in graduate school several decades ago. Except for a bit of armchair empiricism
as they called it the power of personal computers allowed researchers to access
the trade flows collected between all countries at a fine level of
disaggregation. So since those early days the use of
that data has transformed the field as well as
informed work in communication, political science, and other areas. Today, sources of
big data and the ability to process such data means that we can track not only
flows of goods between countries but the flows of information between people.
There are almost as many cell phone subscriptions (6.8 billion) as the 7
billion people on earth and a considerable portion of these users
leave a record of the economic and social interactions through digital and
social media usage. Research by one of our colleagues here at UC Davis shows
that the world's technological capacity to store such information grows at some
25 percent per year reaching about 5 zettabytes by 2014. This
is 5 times more information than all DNA stored in all cells of all humans and is
quickly approaching the amount of information stored by all life on the
planet. So indeed I think we're challenging the biological and even the
physical sciences in terms of the information available and our ability to
process it. Almost a decade ago was the publication of 'Computational Social
Science', an influential article co-authored by one of our participants
that appeared in science in 2009, and it's time to take a step back and
reflect on this revolution. What have we learned? What traditional research
approaches are no longer meaningful and what new questions are we able to ask
and answer? How should we restructure higher education curricula in the social
sciences to embrace computational social science? What are the roles and
responsibilities of the private and public sectors in the new paradigm? And
what will social science look like in the future? These are the questions we
will tackle today as we look ahead to the next decade of research in
computational social science. Before I hand over the floor to my colleague
George Barnett I'd like to thank the Institute for Social Sciences the
Computational Communication Research Lab and the faculty committee in the
Department of communication for all their hard work in making this
event possible. And of course thank you to all of you for your part in what I'm
sure will be a highly productive day. Let me turn the floor over to George.
Thank you. Thank you Rob. It should be noted that it Rob provided me data for a
recent study that I'm doing on international trade and GMO crops and
he's great thank you. As the old guy in the room it is my pleasure to welcome
everyone to UC Davis and this workshop on computational social science.
I originally thought of this workshop to celebrate and to publicize the newly
established our Computational Communication Laboratory which was
envisioned and implemented by two of the Department of Communication's (and indeed
the social sciences') bright young scholars: Martin Hilbert wherever you are
Martin and Cindy Shen. CIndy Shen and Martin Hilbert who are the lab's
co-directors, Jigwen Zhang and myself want to thank
Robert Bell in the Department of Communication and the Institute for
Social Sciences (Joe Dumit, Vicky Austin and Jeremy Till) for their financial and
intellectual support as well as all of today's participants for their
contributions. Computational Social Science is important because it
represents the future and as we will see in a few minutes
it is expertly being practiced today I hope you share my excitement for today's
events. Thank you.
So I'm going to say a few words about the organization of our morning. So we
invited a diversity of perspectives, from computer scientists to engineers and
social scientists to the room today, and as Nosher illustrated his
research yesterday that diversity creates creativity which I'm very much
looking forward to today. So we kind of lossely organized people's presentations
into three panels. The first panel provides kind of overview of perspectives.
The second panel are from scholars who do empirical work using big data and
a third panel is generally about experimental approaches and agent-based
models. So in order to ensure that everybody can have enough time to talk
about their own perspective and their own work we're going to strictly enforce
the five-minute rule so Vicky the assistant director of ISS here has a
cowbell -- you know, very Davis -- and at the four minutes yes thank you
add four minute mark she's going to ring it once at a five minute mark she's
going to ring three times and that time if you do not stop we'll take the
microphone. Okay so we're really going to reinforce this rule and we asked all our
panelists to sit in this front row and after all the panelists had their five
minutes and we'll invite them to sit in front so that on a stage so that we
can open up for discussion.
Hi, I'm Jigwen Zhang, so I'll talk a little bit about
organization in the afternoon. So in afternoon we'll all of us will break out
into four small groups to have focused discussion and so for four important
topics for today's workshop so one is the research innovation in computational
social science and second one is the higher education and what we think about
higher education for computational social science and we also have another
group to talk about private and public sectors roles in doing
research with a combination of social science. The last group will be
talking about the future of social science in the next 50 to 100 years so
in the two-hour focused discussion we hope to gather insights from every
speaker so in the end we can reach some conclusions and recommendations for
conditional social science. It's important to notice that the different
small discussion groups will take place in different rooms so you have to find
the specific room location in your program and each of us will lead one
small group discussion. So I will be in the research innovation group and Cindy
will be in the future of the social science, Martin will be in a group for
talking about private and public sector roles, and George will lead the
discussion on higher education for computational social science. So then
Martin will come and talk about what we hope to get out of this workshop as a
collective.
Thank you I'm Martin Hilbert welcome everybody thanks for
coming so now Cindy talked about what we're
going to do in the morning and as you already see the format is quite
unique in the sense that the nobody gets to speak longer than five minutes and
that has a purpose. Then of course in the afternoon the workshops the different
four different working groups also has a purpose and that purpose at the end
focuses on what we have as a final product after that and of course
being very inspired by this very well known publication that was
conceptualized now almost ten years ago and published in 2009, 'Computational
Social Science', we thought well why don't we take this opportunity not only to
present each other's views but really work and get something out of that that
goes beyond what each one individually can bring to the table and I'm sure each
one of us could right now sit down and write a small opinion piece about the
importance of computational social science. It is
extremely impressive that we have this group that each one of us could do that
and our ambition now is, well, can we even go beyond that and get some results
that are maybe counterintuitive, that are really uniquely new and
can contribute to this discussion and we really want to have the ambition to work
on that, be it in the morning by listening quickly to very varied more than twenty
different perspectives and get the input and in the afternoon to sit down with
Google Docs we prepared four Google Docs and nowadays that is possible to work
collectively on them and already almost kind of like conceptualize maybe what
potentially could be four different sections of an opinion piece that
hopefully then people will also want to continue after that and finish that up
and continue to co-author that piece together and hopefully we come out
with something quite unique that might also be interesting for the wider
community. So that's actually the goal and that's why the kind of like
unconventional design of the workshop is very small very short
presentations and then with intensive working groups in the afternoon okay
thank you very much for that um with that, I give to one of ours Raisa D'Souza
for the for the first presentation.