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  • 00:00

    [MUSIC PLAYING]

  • 00:10

    GIUSEPPE VELTRI: Hello.My name is Giuseppe Veltri.I'm a professor in research methodology at the Universityof Trento in Italy.And I've been working with big data and digital researchfor quite a few years now.And I think I'm really interested in the possibilityof big data and computational methods,because during my graduate years, when

  • 00:32

    GIUSEPPE VELTRI [continued]: I was a student at the LSE, the London School of Economics,we always had to face a situation of data scarcity.It was always difficult to find data and to do research.So developability of data is definitely one of the aspects,but it's also the changes of new methodsthat are coming from different disciplines,

  • 00:54

    GIUSEPPE VELTRI [continued]: like for example, computer science,that is challenging the way we used to do research.And I think that this sort of contaminationis really, really interesting.Because it doesn't mean to substitute the methodologywe used to have, but to complement themwith other aspects.And this is something that for new researchers is I think,

  • 01:17

    GIUSEPPE VELTRI [continued]: crucial.Because it's a set of competenciesthat now needs to be part of the toolboxthat students and people that like to be researchers,want to, they need to acquire.I also think a lot of the fears about acquiringthese skills are misplaced.Because in reality, a lot of I think,

  • 01:38

    GIUSEPPE VELTRI [continued]: social science students have the kind of mindsetand already there's some basic trainingthat would help them to acquire some of these skills.And so it's part of what is goingto be social science in the next 10, 20 years,to be part of not only to master some of these techniques,

  • 01:59

    GIUSEPPE VELTRI [continued]: but to be able to work with people that perhaps are morespecialized.But you are able to talk with themthis sort of same language.At the same time, I think it's important for social scientiststo remain part of this process of developing new methodology.Also to be critical and to help develop together,rather than either in competition or in opposition

  • 02:21

    GIUSEPPE VELTRI [continued]: to people coming from computer science or data sciencenowadays.So we want to be part of this process,rather than being excluded or sort of createa conflict that basically there's no need to be.I think also that competition, such as science, which

  • 02:41

    GIUSEPPE VELTRI [continued]: is the label that nowadays definesthis contamination of computational methodsinto social science, opens up new perspectives about the waywe can revise a lot of our theories and models, whichwere based on scarcity of data.And therefore, I think really constrain

  • 03:02

    GIUSEPPE VELTRI [continued]: us to focus on models that they were notvery well prepared to explain, for example, dynamic processes.Simply because to collect data in [INAUDIBLE]longitudinal terms was very difficult, very expensive.And now this is a possibility.That's something we can do.So I think there are exciting opportunities.

  • 03:24

    GIUSEPPE VELTRI [continued]: There are also a lot of questions about accessto data, about issues of privacy,issues of ethical aspects of researchand needs to be addressed.But again, that's where social scientists can play a role.We had a debate about these issues for a long time.So I think we can contribute to this.

  • 03:46

    GIUSEPPE VELTRI [continued]: So on balance, I think there is much more to gain rather thanto lose in trying to engage with this new way of doingsocial science.So I would strongly encourage people to at least tryto think how these new methodologiesand new approaches can benefit the research they already do.

  • 04:08

    GIUSEPPE VELTRI [continued]: Because not only, I think it helps to formulate new researchquestions, but might also help to reframe in a different wayall the research questions that people had and they'vedone you know in the past.I think now training is becoming much more accessible.There's a lot of resources.

  • 04:32

    GIUSEPPE VELTRI [continued]: In many, many degrees already, there theyare integrating some kind of trainingto prepare you to then develop your own, if you want,computational method skills.But my position is that you don't have to become a computerscientist, you have to become someone who canwork with a computer scientist.

  • 04:53

    GIUSEPPE VELTRI [continued]: And therefore, I think that's much more possible.And the fears related to the fact of,for the retraining that people have to go through,are unjustified in my opinion, because exactly nobody'sasking a social scientist, a sociologist, a psychologist,to become a computer scientist.

  • 05:13

    GIUSEPPE VELTRI [continued]: But just to be aware of what is done in those fieldsand potentially work with them.Computer scientists obviously, theydevelop a lot of their techniquesin a different context.So some of the way how they use their methodsin the social domain could be problematic.I mean, we have learned that to study

  • 05:38

    GIUSEPPE VELTRI [continued]: essentially human behavior or social reality,is extremely tough.People are strategic.They respond to your attempts to measure what they do.Often what they appear to be clear cut indicators,they are not.So I think there is this, the need of having a better

  • 05:58

    GIUSEPPE VELTRI [continued]: understanding of also the theoretical aspectsof research.I think someone said a long time ago,there is nothing more practical than a good theoryto guide the way you do research.And I think still that's the case.So yes, I think it should be a relationship that

  • 06:18

    GIUSEPPE VELTRI [continued]: is among equals so to speak.So there is a process of mutual learningbetween both the areas.And I think the best computational social scienceI've seen, usually comes out of a collaboration in these terms,where both, they tend to converge to a common ground.So far, a lot of effort has been in to creating

  • 06:40

    GIUSEPPE VELTRI [continued]: this common ground between computerscience and social science to address typical issuesof social science research.But I think a lot of work needs to be done,and hopefully will happen in a kind of impact thatcan have for policy, and therefore

  • 07:00

    GIUSEPPE VELTRI [continued]: for outside academic domain where there are really,let's say, there is a problem of linking evidence with policy.There is a problem of exploiting the best way a lotof data that actually are available.

  • 07:21

    GIUSEPPE VELTRI [continued]: One of the things I was discussingwith a few colleagues in these days,is that there is a lot of data in public administrationsacross different countries, and so a lot of datasets and databases.Are not linked up.And so, in fact, you already have the data,but nobody has done the effort of,which is actually a sort of big data effort in bringing

  • 07:43

    GIUSEPPE VELTRI [continued]: these data together and then analyze them in a new way.And this is something that I see as oneor the potential application of the future.So computational social science for policy support,if you want.I think one of the way computational social sciencewill evolve, is in increasing the kind of support

  • 08:07

    GIUSEPPE VELTRI [continued]: it can give to policy.So computational social science for policy support.And I think this is key also, because it kind of movesfrom the domain of just kind of basic research to alsoapplied research, which is I think crucial these daysalso for the fact that more and more academics are

  • 08:28

    GIUSEPPE VELTRI [continued]: accountable for funding.And therefore, they need to justify why money hasbeen spent in social research.And therefore, how they contributeto the understanding or the solving of societal issues.So overall, I think that's an important aspect.The other one is obviously that we have,

  • 08:50

    GIUSEPPE VELTRI [continued]: I think, a long-term plan of revisionof a lot of theoretical models in social sciencethat could change substantially, thanksto the new methods we have to analyze dataand the new ways we have to collect data.[MUSIC PLAYING]

Video Info

Publisher: SAGE Publications Ltd

Publication Year: 2019

Video Type:Interview

Methods: Interdisciplinarity

Keywords: collaboration; interdisciplinary studies; internet data collection; research methodology; retraining; Social policy; Social science research; technology and careers; training and skill acquisition ... Show More

Segment Info

Segment Num.: 1

Persons Discussed:

Events Discussed:

Keywords:

Abstract

Giuseppe Veltri, Professor of Research Methodology at the University of Trento, explains that big data has solved one of the problems that social scientists often faced—data scarcity—but to access this data resource, social scientists must learn the language of data science, and collaborate with data scientists in developing relevant methodology for data collection and research.

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Giuseppe Veltri Discusses Computational Social Science & Interdisciplinary Collaborations

Giuseppe Veltri, Professor of Research Methodology at the University of Trento, explains that big data has solved one of the problems that social scientists often faced—data scarcity—but to access this data resource, social scientists must learn the language of data science, and collaborate with data scientists in developing relevant methodology for data collection and research.

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