Computing in Social Science, Arts and Humanities - Science topic

KEY TAKEAWAYS

In my opinion, the current fourth technological revolution is just beginning. Evidence to support this thesis is the ongoing progress in the creation of new advanced technologies Industry 4.0 and their applications in industry, in improving the offering and implementation of services, in improving the organization and functioning of economic entities and financial and public institutions, in improving the management processes of these entities, etc.

Regards,

Dariusz Prokopowicz

The SARS-CoV-2 (Covid-19) coronavirus pandemic has changed the behavior of consumers who shop online more and more frequently.

Regards,

Dariusz Prokopowicz

Read the fundamentals of the research.

Champion, D. J. (1970). Basic statistics for social research. Scranton: Chandler Publishing Company.

Let us share and continue to learn-life-long learners as the best way to improve this mother earth.

The above question inspired me to the following considerations:

Is the progressive increase in the digitization of the education process a feature of the current technological revolution of Industry 4.0?

Is the progressive increase in the digitization of education process instruments a feature of the current technological revolution known as Industry 4.0?Measuring the impact of digital technology, including new online media on the process of learning and the effects of the education process can be based on a comparison of assessments at a specific time, a specific educational process supported by the use of new online media, social media portals and other technologies typical of the digital age. These technologies currently include mainly new technological solutions, streamlining improvements, innovations etc. regarding, among others, advanced data processing, including data obtained from the Internet, data processing in the cloud, Big Data database systems, using artificial intelligence, etc. These new technologies of advanced information processing co-create the current fourth technological revolution called Industry 4.0.In view of the above, the current question is: Is the progressive increase in the digitization of education process instruments a feature of the current technological revolution known as Industry 4.0?

Please, answer, comments.

I invite you to the discussion

Best wishes

Do you know this paper?

Shigeaki Amano, Tadahisa Kondo, and Sachiyo Kajikawa 2001. Analysis on infant speech with longitudinal recordings The Journal of the Acoustical Society of America 110, 2703 (2001);

https://doi.org/10.1121/1.4777322

thanks, Marie!

Indeed, with 'digital classics', one can go in a myriad of ways.  As I developed the course, I took into account my own expertise/interests, while at the same time thinking about the skills of the typical undergraduate classics student. Part of the goal was to introduce to people normally adverse to using a computer outside of word processing the concept of data and means of disseminating information in non-traditional means. I've attached the eventual syllabus and assignments of the course we did in 2013. By no means an end-point, this course will be offered again, certainly with slightly different angles.

One of the things we took away from the class was the wide array of skills that students brought to class. There was a wide range of computational literacy expressed, which made things a bit challenging. When we offer it again, we'll pay closer attention to how and to whom we advertise and recommend for the class.

Analysis of likert scale data such as from 1 (none) to 5 (a lot) can be done by calculating the weighted mean scores of each component (A, B and C) and if component C obtain a higher weighted mean score than A and B you can prove that component C is more helpful in assessing relevance of source page than component A and component B. Further ANOVA can be conducted to check the significant differences.

Dear Nasim

I think your question is a fascinating one, something that I have pondered myself for some time. A key aspect is how you want to evaluate it. In terms of utility, the main focus would be on whether and how people would use it, that is, how useful they find it. Perhaps all you can do is run an trial with a group of people, ie colleagues, students, ask for volunteers on researchgate etc.

Anyway, still thinking about it....

Philip 

I highly recommend works and papers by Epstein and Axtell- computational modeling of social phenomenon, macro structures derived as a generative product  of micro motives/states. Features of recursion and contagion emphasized in their models.

Doran's work on social simulation will provide interesting material for the algorithmic treatment of agents' cognitive psychology.

At a spatial level and within an urban ecology, works by Batty. In particular, visualization features of his simulations.

We used a very simple RL algo in order to add some adpatibility capability to the iCub playing DJ with a human partner which could give feeback about the music quality.

(see the video attached). We never really investigated the effect of this adaptation though...

Hello Carla,

not answering for David - but -

as an artist, and someone reasonably well informed in cognitive, neuroscience and philosophy of mind, the question which preoccupies me in this conversation is "why are we treating 'looking at art' as a special kind of looking?" And with respect to what?

Until we answer that question, it seems to me that any experimental 'findings' will be dubious and any  decision to follow a particular methodology 'topsy-turvy' or theoretically dubious.

It seems that scientist are often willing to accord something they call 'art' special status. Some artists have 'science-envy' and some scientists have 'art-envy'. Both seem based in some sort of insecurity and probably anachronistic information. For instance, take Joseph Kosuth's canonical conceptual art work 'one and three chairs' which consisted of: a chair, a black and white photograph of the chair, and a textual description of the chair. All three were chosen to avoid any aesthetic quality. It was an ordinary chair, the photograph was deadpan.

The specific point is that while being 'art' the work sought to avoid any of the trappings of 'art'. That is a general characteristic of progressive art. For the Venice Biennale a couple of years ago, a couple of guys dragged a row boat over the alps.

The general point - if we are talking about 'art' from a vision point of view, 'art vision' is  no different from any other kind of vision because 'art' can take any form - or non-form.

If on the other hand, we are talking about 'looking at pictures', then lets try to be clear about what distinguishes an art picture from a non-art picture. I suspect we would be drawn into the same kind of regress because many artists, perverse as they are, try to make art pictures indistinguishable from non-art pictures. I had a grad student whose graduation work consisted of the restaging of mail-order catalog pictures, pictures which have no pretense to art.

best

Simon

Hello Saima I dont know Tobii T120 eye tracker, the one they use for the experiment (van Rijn mail, Barendse, Goozen, Swaab), but it seems, that its all done. Using that technology you can report  a heat map without programming it for example

In these sense the authors said about the experiemnt

"Gaze data were processed using Tobii Studio (3.0), using the Tobii I-VT fixation filter. The ‘Dynamic AOI (Area of Interest)’ tool, using freeform shapes, was used to draw AOI's. Dynamic AOIs were grouped into the following categories: facial features (without mouth and eyes), eyes, mouth, body, objects and other (i.e. on the screen, outside other AOI's)."

Also you can work with the Eye Tribe

https://theeyetribe.com/ and test heat map making an account in Eyeproof

When you referer to: "mathematical computations that eye tracking system", what you will need to finish your study? In my case is a little bit more complex Im finishing I hope a first aproach of my research the next week a theorical one. Then I rebuild a software that can detect bad words written by childs with aphasia / SLI. Finally I will meassure empathy.  But all works and people are welcome!

best,

--in

But MIRT is more useful at the estimation of groups, not individual persons

To be honest I can hardly imagine any connection between your research goal 'testing the trust of people' and your request for 'downloading a container, include a secret and pick a strong password'.

What do you want to evaluate?

If users put in a 'real secret' or just some random data?

How do you want to appraise if the data is a secret or not?

This is a good question especially since interest in CS as a research method has seen some notoriety in recent years.

I've experimented with 2 pilots on Mturk and am just wrapping up my data collection on Crowd Flower for my dissertation. My second pilot may be of interest to you since I completed my pilot in both online and in-person settings with comparable results:

Look at articles by Lefever, Griffiths, Granello and Beaudoin regarding online research (not specific to CS) and there is every indication that anonymity can actually increase trust in survey answers (in particular those about SES) and there is also the added benefit of a decrease in survey bias.

Of course there are always those who will wish to provide obstructionist replies and subvert your research BUT the geographical and cultural diversity of your participant pool counters many of the detractors.

Although I've not had a chance to look at my latest data exclusively for this issue, there are a few things I've noticed. Since Crowd Flower has no quality control (as Mturk does) I was only able to achieve about 50% 'good' data meaning that the participants followed my instructions, filled out the survey and provided me with drawings. The main issue I had was many providing photos that were not theirs, however even those that did not follow instructions and provided photos still appear to have answered the survey questions truthfully (some of this I garnered by matching IPs to the location they provided in the survey). Within this half of participants roughly 10%+ seemed to complete the survey without any concern for the questions. It's also important to note that this fluctuates from region to region. For example larger more tech-savvy populations tended to have more of these obstructionist users who know the crowdsourcing system well and how to use/abuse it.

There is still very little literature on this emerging research niche and I'm looking forward to pursuing it further in the future.

Have you used any of the CS platforms for research?

Hi Tahir, some people whose work on speech emotion you may want to check include Eduardo Coutinho (e.g. https://www.academia.edu/1087299/Psychoacoustic_cues_to_emotion_in_speech_prosody_and_music), Petri Laukka (http://w3.psychology.su.se/staff/pela/), and Klaus Scherer (http://www.affective-sciences.org/user/scherer).

I will also mention one work of mine even though it is more towards art/design rather than generalisable analysis (https://www.academia.edu/842766/About_TreeTorika_Rhetorics_CAAC_and_Mao._book_chapter_) and perhaps of lesser interest to you. Have fun researching!

Dear Gerard,

Some additional relevant papers might be the following:

Jhala, A. (2008). Exploiting Structure and Conventions of Movie Scripts for Information Retrieval and Text Mining. In Interactive Storytelling (pp. 210-213). Springer Berlin Heidelberg.‏

Walker, M. A., Lin, G. I., & Sawyer, J. (2012). An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style. In LREC (pp. 1373-1378).‏

Kundu, A., Das, D., & Bandyopadhyay, S. (2012, December). Speaker identification from film dialogues. In Intelligent Human Computer Interaction (IHCI), 2012 4th International Conference on (pp. 1-4). IEEE.‏

Kundu, A. (2013). Identification of Speakers and Scenes from Movie Dialogue(Doctoral dissertation, Department of Computer Science and Engineering, Jadavpur University, India).‏

Agarwal, A., Balasubramanian, S., Zheng, J., & Dash, S. (2014). Parsing Screenplays for Extracting Social Networks from Movies. EACL 2014, 50-58.‏

Best regards,

Yaakov

@Iskandar, thanks for listing the steps to achieving this task. I am looking for exactly these linguistic rules which you have mentioned. Can you cite some work or links where I can find some information on this? Thanks.

@Osman, as the Stanford group is pretty big, can you please give me a link to the person/team at Stanford that is working on this or better, some paper(s) or work that is related to this? Thanks.

Maybe you can use Checkland’s soft systems methodology that were used on Knowledge Management Research Using Grounded Theory Strategy: Applicability,

Limitations and Ways Forward by WALTER OMONA* from http://cit.mak.ac.ug/iccir/downloads/ICCIR_10/WALTER%20OMONA_%20Theo%20van%20der%20Weide_%20Jude%20T%20Lubega_10.pdf.

It seems to be a good and grounded theory for KM Reseach.

Or article here in researchgate BUILDING A QUALITATIVE RESEARCH METHODOLOGICAL STRATEGY TO UNDERSTAND KNOWLEDGE MANAGEMENT IN THE BRAZILIAN ORGANIZATIONAL CONTEXT: MULTIPLE CASE STUDIES FOR THE PROPOSITION OF AN INTEGRATIVE CONCEPTUAL MODEL

THE ICOM-CIDOC newsletter is always published in English and French. All the articles are translated. You can find all the back issues here: http://network.icom.museum/cidoc/archives/past-newsletters/

I'm a PhD student at George Mason's Computational Social Science department, first dedicated department in the US. Yes, finding students with strengths in multiple disciplines isn't easy, esp. since there are so many incentives to "stove pipe". But they are out there, often on the fringes of the academic and professional world because they don't "fit the mold". Best way to find them is to create a "honey pot" to attract them.

I'll second Yoshinori Shiozawa's idea of hosting participatory games. For business students, the Beer Game is a good choice, and has been used for decades. For social science students, there are nice examples in the NetLogo library that could be set up as network games. I'd guess that there are also artificial stock market games that could arouse interest.

But here's a different angle: Find some pressing economic problem that is specific to your region and your country and that calls out for a computational approach. Then organize a workshop with local business and government officials who can talk about it and make it vivid. Invite guest speakers who are well-known in Computational Social Science and have them lead panel discussions or breakout sessions on how the problems might be framed using computational methods. IDEALLY, you'd find some sponsor to put up money to fund a project, or even a contest prize (~$3,000 US would be enough) and then have a second workshop in 6 months to show off team results.