RE: [Air-l] Technical competence
Long-time reader, first-time poster. :-) I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes? In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction. Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
Yes, I'd agree with this - it can be useful to understand something of how any particular technical medium is productive in online social formations, but find it far more useful to approach social software primarily from the point of view of the user. The users will always manage to exceed the developers' constructs anyway. Conversely, I find it really interesting how social softwares materialise the culture of their developers whilst users will often try to use it according to the needs of a completely different culture. Paula Ledbetter, Andrew Michael wrote:
Long-time reader, first-time poster. :-)
I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes?
In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction.
Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
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But let's consider the recent issue of archiving websites -- clearly we need some kind of technical competence for that. Ditto link analysis. Ditto for reading others' papers and understanding whether they've used a correct or appropriate methodology. For example, in understanding the so-called popularity of a website people should know to differentiate between 'hits' and 'pages' and 'visitors' and should be able to figure out whether robots have been excluded - to take a random example that demands a bit of specialised knowledge. Shouldn't this be the kind of thing we are considering for our students? Elizabeth On 6 Jun 2005, at 22:34, Paula wrote:
Yes, I'd agree with this - it can be useful to understand something of how any particular technical medium is productive in online social formations, but find it far more useful to approach social software primarily from the point of view of the user. The users will always manage to exceed the developers' constructs anyway.
Conversely, I find it really interesting how social softwares materialise the culture of their developers whilst users will often try to use it according to the needs of a completely different culture.
Paula
Ledbetter, Andrew Michael wrote:
Long-time reader, first-time poster. :-)
I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes?
In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction.
Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
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Elizabeth Van Couvering PhD Student Department of Media & Communications London School of Economics and Political Science http://personal.lse.ac.uk/vancouve/ e.j.van-couvering@lse.ac.uk
That was the point I was trying to make. If the planned research requires some sort of special techniques then the researcher and supervisor) must ensure that they are knowledgeable in that area. Although it is impossible to predict all the skills needed at the outset a fair number of them can be forseen. We cannot educate students in every area that they are possible to come across in their research-our students must learn how to learn. After all some techniques will be required at a particular period of time. Elizabeth you cited Pascal programming as one of your skills but I bet you would be hard pressed to find any requirements for that knowledge now. It is the more abstract skill of programming and analysis that is more valuable. Likewise I studied a fair amount of statistics in my early years but now I like to employ qualitative methods. It was a skill I had to learn as I was doing my research. Remember, one of the things about undertaking a PhD is that the student is not only discovering facts about some phenomena but also learning how to undertake a larger research project. That is learning research skills. Andrew W. -- email: andrewwenn@mac.com internet: http://homepage.mac.com/andrewwenn/ On 07/06/2005, at 6:39 PM, Elizabeth Van Couvering wrote:
But let's consider the recent issue of archiving websites -- clearly we need some kind of technical competence for that. Ditto link analysis. Ditto for reading others' papers and understanding whether they've used a correct or appropriate methodology. For example, in understanding the so-called popularity of a website people should know to differentiate between 'hits' and 'pages' and 'visitors' and should be able to figure out whether robots have been excluded - to take a random example that demands a bit of specialised knowledge. Shouldn't this be the kind of thing we are considering for our students?
Elizabeth
On 6 Jun 2005, at 22:34, Paula wrote:
Yes, I'd agree with this - it can be useful to understand something of how any particular technical medium is productive in online social formations, but find it far more useful to approach social software primarily from the point of view of the user. The users will always manage to exceed the developers' constructs anyway.
Conversely, I find it really interesting how social softwares materialise the culture of their developers whilst users will often try to use it according to the needs of a completely different culture.
Paula
Ledbetter, Andrew Michael wrote:
Long-time reader, first-time poster. :-)
I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes?
In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction.
Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
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Elizabeth Van Couvering PhD Student Department of Media & Communications London School of Economics and Political Science http://personal.lse.ac.uk/vancouve/ e.j.van-couvering@lse.ac.uk
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Yes learning to learn is important. But not to flame but to offer counter examples. In my non internet reading on qualitative research in schizophrenia recovery I read Larry Davidson's Living Outside Mental Illness (New York: New York University Press, 2003). In his study interviews were recorded and then common themes in the text were statistcally analysed or basically counted. Larry also does quite a lot of chapters on methodology in his book. This would be the deepest I know qualitiative research I think. But qualitiative and quantitative can be mixed well. Now Pascal and this is more a novel point. I was reading some conference proceedings from the computer science field on searching the web with XML. In particular a Pascal like script was described and written in one paper that searched for MathML documents on the web and the aim was to produce a collection of knowledge. The pascal script would gather web published math results and gather these. We have a global library but need to access it right? I have been told fortran is a dead language by some by others that it is alive and well in industry. This all makes sense if one considers the number of computers in use is increasing there is more diversity these days. Now I will venture into a grip maybe technical, consider the web as collection of knowledge. Why do we need a collection of knowledge? There are many answers but I don't think computer scientists even ask the why questions which is what social scientists and philosophers can ask. Also another grip HTML wwas considered the best most universal system for information distribution but now XML is the new ideal. Certainly knowing the basics of html or XML lets one see the reasons for the pursuit of these data formats which each in their time get a lot of effort and fill up a lot of Internet production time. Peter Timusk B.Math Just trying to stay linear www.crystalcomputing.net >blog> http://logbook.crystalcomputing.net www.webpagex.org >blog> http://notebook.webpagex.org
The need for knowing about computer technologies in communications research is becoming greater than the rudiments of web composition and traffic analysis. Already, artificial intelligence is being applied to content analysis, as in the case of a number of papers published on the Enron email corpus. The skill sets involved fall outside those typically found among communications researchers. A principle researcher in one of these Enron studies is Andrew McCallum at UMass, who is a physicist iirc. Another physicist, Andrew Smith, is responsible for the Leximancer tool mentioned earlier by Thomas Koenig. Less abstract tools like structural equation modeling are common now, and require competence in computer technologies beyond SPSS. Whether these technologies should be incorporated in curricula is maybe not the right question, as they are not the types of skills one gets in a course or two. Perhaps the field should recruit from among information science and computer science undergrads who come equipped with the skills already. -----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Elizabeth Van Couvering Sent: Tuesday, June 07, 2005 4:40 AM To: air-l@listserv.aoir.org Subject: Re: [Air-l] Technical competence But let's consider the recent issue of archiving websites -- clearly we need some kind of technical competence for that. Ditto link analysis. Ditto for reading others' papers and understanding whether they've used a correct or appropriate methodology. For example, in understanding the so-called popularity of a website people should know to differentiate between 'hits' and 'pages' and 'visitors' and should be able to figure out whether robots have been excluded - to take a random example that demands a bit of specialised knowledge. Shouldn't this be the kind of thing we are considering for our students? Elizabeth On 6 Jun 2005, at 22:34, Paula wrote:
Yes, I'd agree with this - it can be useful to understand something of how any particular technical medium is productive in online social formations, but find it far more useful to approach social software primarily from the point of view of the user. The users will always manage to exceed the developers' constructs anyway.
Conversely, I find it really interesting how social softwares materialise the culture of their developers whilst users will often try to use it according to the needs of a completely different culture.
Paula
Ledbetter, Andrew Michael wrote:
Long-time reader, first-time poster. :-)
I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes?
In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction.
Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
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Elizabeth Van Couvering PhD Student Department of Media & Communications London School of Economics and Political Science http://personal.lse.ac.uk/vancouve/ e.j.van-couvering@lse.ac.uk _______________________________________________ The Air-l-aoir.org@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/
Just because some folks are applying advanced techniques to data, doesn't mean that anyone (much less everyone) else needs to understand those techniques. Frequently, methods employed in the social sciences surpass the theoretical maturity available. Perhaps I'm archaic to think that techniques should test ideas, rather than generate them. But even factor analysis and stepwise regression give me pause - not because I lack the technical competence, but because sampling deviations may generate findings that won't hold beyond the available sample. -eg
-----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Cox Sent: Tuesday, June 07, 2005 4:23 AM To: air-l@listserv.aoir.org Subject: RE: [Air-l] Technical competence
The need for knowing about computer technologies in communications research is becoming greater than the rudiments of web composition and traffic analysis. Already, artificial intelligence is being applied to content analysis, as in the case of a number of papers published on the Enron email corpus. The skill sets involved fall outside those typically found among communications researchers. A principle researcher in one of these Enron studies is Andrew McCallum at UMass, who is a physicist iirc. Another physicist, Andrew Smith, is responsible for the Leximancer tool mentioned earlier by Thomas Koenig. Less abstract tools like structural equation modeling are common now, and require competence in computer technologies beyond SPSS.
Whether these technologies should be incorporated in curricula is maybe not the right question, as they are not the types of skills one gets in a course or two. Perhaps the field should recruit from among information science and computer science undergrads who come equipped with the skills already.
Excellent points, especially the tenet that we should be testing ideas, in my mind, hypotheses. To expand on your last argument a bit, it seems to me that these new techniques, while fundamentally Baysean in nature, are poorly enough understood that they invite skepticism. Some even use proprietary algorithms making it impossible to know the certain meaning of results. Still, I can't help thinking progress in studies using content analysis would accelerate by their adoption where the bottleneck is what to do with the volumes of raw data acquired as 'scrubbed' content from online sources. Sticking with manual coding means that only linear growth is possible. -----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Ellis Godard Sent: Tuesday, June 07, 2005 3:22 PM To: air-l@listserv.aoir.org Subject: RE: [Air-l] Technical competence Just because some folks are applying advanced techniques to data, doesn't mean that anyone (much less everyone) else needs to understand those techniques. Frequently, methods employed in the social sciences surpass the theoretical maturity available. Perhaps I'm archaic to think that techniques should test ideas, rather than generate them. But even factor analysis and stepwise regression give me pause - not because I lack the technical competence, but because sampling deviations may generate findings that won't hold beyond the available sample. -eg
-----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Cox Sent: Tuesday, June 07, 2005 4:23 AM To: air-l@listserv.aoir.org Subject: RE: [Air-l] Technical competence
The need for knowing about computer technologies in communications research is becoming greater than the rudiments of web composition and traffic analysis. Already, artificial intelligence is being applied to content analysis, as in the case of a number of papers published on the Enron email corpus. The skill sets involved fall outside those typically found among communications researchers. A principle researcher in one of these Enron studies is Andrew McCallum at UMass, who is a physicist iirc. Another physicist, Andrew Smith, is responsible for the Leximancer tool mentioned earlier by Thomas Koenig. Less abstract tools like structural equation modeling are common now, and require competence in computer technologies beyond SPSS.
Whether these technologies should be incorporated in curricula is maybe not the right question, as they are not the types of skills one gets in a course or two. Perhaps the field should recruit from among information science and computer science undergrads who come equipped with the skills already.
_______________________________________________ The Air-l-aoir.org@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/listinfo.cgi/air-l-aoir.org Join the Association of Internet Researchers: http://www.aoir.org/
For once we more or less agree! ;-) Ellis Godard wrote:
Just because some folks are applying advanced techniques to data, doesn't mean that anyone (much less everyone) else needs to understand those techniques. Frequently, methods employed in the social sciences surpass the theoretical maturity available. Perhaps I'm archaic to think that techniques should test ideas, rather than generate them. But even factor analysis and stepwise regression give me pause - not because I lack the technical competence, but because sampling deviations may generate findings that won't hold beyond the available sample.
-eg
-----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Cox Sent: Tuesday, June 07, 2005 4:23 AM To: air-l@listserv.aoir.org Subject: RE: [Air-l] Technical competence
The need for knowing about computer technologies in communications research is becoming greater than the rudiments of web composition and traffic analysis. Already, artificial intelligence is being applied to content analysis, as in the case of a number of papers published on the Enron email corpus. The skill sets involved fall outside those typically found among communications researchers. A principle researcher in one of these Enron studies is Andrew McCallum at UMass, who is a physicist iirc. Another physicist, Andrew Smith, is responsible for the Leximancer tool mentioned earlier by Thomas Koenig. Less abstract tools like structural equation modeling are common now, and require competence in computer technologies beyond SPSS.
Whether these technologies should be incorporated in curricula is maybe not the right question, as they are not the types of skills one gets in a course or two. Perhaps the field should recruit from among information science and computer science undergrads who come equipped with the skills already.
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Anyone who's ever read any FLOSS documentation will appreciate that physicists are not necessarily the most fluent analysists or writers if the topic is user experience ;-) Paula Cox wrote:
The need for knowing about computer technologies in communications research is becoming greater than the rudiments of web composition and traffic analysis. Already, artificial intelligence is being applied to content analysis, as in the case of a number of papers published on the Enron email corpus. The skill sets involved fall outside those typically found among communications researchers. A principle researcher in one of these Enron studies is Andrew McCallum at UMass, who is a physicist iirc. Another physicist, Andrew Smith, is responsible for the Leximancer tool mentioned earlier by Thomas Koenig. Less abstract tools like structural equation modeling are common now, and require competence in computer technologies beyond SPSS.
Whether these technologies should be incorporated in curricula is maybe not the right question, as they are not the types of skills one gets in a course or two. Perhaps the field should recruit from among information science and computer science undergrads who come equipped with the skills already.
-----Original Message----- From: air-l-aoir.org-bounces@listserv.aoir.org [mailto:air-l-aoir.org-bounces@listserv.aoir.org] On Behalf Of Elizabeth Van Couvering Sent: Tuesday, June 07, 2005 4:40 AM To: air-l@listserv.aoir.org Subject: Re: [Air-l] Technical competence
But let's consider the recent issue of archiving websites -- clearly we need some kind of technical competence for that. Ditto link analysis. Ditto for reading others' papers and understanding whether they've used a correct or appropriate methodology. For example, in understanding the so-called popularity of a website people should know to differentiate between 'hits' and 'pages' and 'visitors' and should be able to figure out whether robots have been excluded - to take a random example that demands a bit of specialised knowledge. Shouldn't this be the kind of thing we are considering for our students?
Elizabeth
On 6 Jun 2005, at 22:34, Paula wrote:
Yes, I'd agree with this - it can be useful to understand something of how any particular technical medium is productive in online social formations, but find it far more useful to approach social software primarily from the point of view of the user. The users will always manage to exceed the developers' constructs anyway.
Conversely, I find it really interesting how social softwares materialise the culture of their developers whilst users will often try to use it according to the needs of a completely different culture.
Paula
Ledbetter, Andrew Michael wrote:
Long-time reader, first-time poster. :-)
I agree, interesting question, and an important question. I think the (a) particular research question and (b) population under study significantly influence the level of technical competence a researcher would need. And we must not forget that the vast majority of web users, e-mail users, online gamers, etc. do not know much at all about UNIX, perl, Java, or probably even basic ideas about how the TCP/IP protocol operates. Given this, might there be occasions where lacking in-depth computer science knowledge might actually help a researcher approaching the Internet from a social science perspective, since they may be able to more easily view the technology through the users' eyes rather than the developers' eyes?
In my own research, I find that my computer science background helps me understand the contours of how the nature of a technology encourages and discourages certain forms of social interaction... but I find that my social science background helps me far more in understanding how human beings appropriate the technology in their social interaction.
Andrew ------------- Andrew M. Ledbetter Ph.D. student, University of Kansas Department of Communication Studies aledbett@ku.edu
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Elizabeth Van Couvering PhD Student Department of Media & Communications London School of Economics and Political Science http://personal.lse.ac.uk/vancouve/ e.j.van-couvering@lse.ac.uk
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participants (7)
-
Andrew Wenn -
Cox -
Elizabeth Van Couvering -
Ellis Godard -
Ledbetter, Andrew Michael -
Paula -
Peter T.