Fiches de cours 2017-2018

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Quantification of user experience

DH-402

Enseignant(s) :

Boullier Dominique Georges Léon

Langue:

English

Summary

The course will deliver all the conceptual and technical resources required for managing a user-centered design process that depends more and more on sophisticated quantification methods.

Content

User experience is the target and the resource of the digital economy: provide new valuable experience, get the feedback from traces and tests, trigger the contribution from online communities and reinvent the product, the service, the content. Digital Humanities provide new attractive user experiences. They also design the sensors, the traces, the tests, the metrics and the concepts for understanding user's behavior. The course will deliver all the conceptual and technical resources required for managing a user-centered design process that depends more and more on sophisticated quantification methods.

Content:

1/ History of cognitive technologies and innovations  (session 1 and 2)

a/ Historical landmarks in  cognitive technologies

Goody: writing

Eisenstein: printing

Panofsky and Alpers: perspective

b/ History and sociology of innovations

(related to content industry and UX)

Telecoms, computer interfaces, internet, photography, music. Technical evolution and business models

2/ Cultural differences in user experience (session 3 and 4)

a/ A primer on anthropology and theories of representation

Descola (four ontologies)

Translation : linguistic and cultural stakes and theories

Digital experience around the world (the phone as the universal device or not?)

Culturonomics ( Manovich)

b/ Sociotechnical analysis of innovations and appropriation processes

Theory of diffusion (Rogers)

Appropriation and reinvention : case studies and strategies

Generation gap: learning by immersion, imitation and training, primer and secondary socialization processes.

3/Cognitive and semiotics dimensions of UX (session 5 and 6)

a/ Perception, memory and attention

Perception: salience, features

Gestalt theory

Learning processes

Problem solving and decision theories

Distributed cognition approaches (Suchman, Hutchins)

Human-Machine Interaction theories and methods

Attention economy

b/ Semiotics

Index, symbol, sign (Peirce)

Structural semiotics (Greimas) and narratology

Graphic semiology (Bertin)

Data viz issues and concepts (tables, timelines, maps, and dashboards)

4/ Quantification and feedback of UX (session 7, 8 and 9)

a/ Big Data in quantification history: statistics, surveys, polls and social listening. (Desrosières)

Propagation and memetics metrics (Kleinberg, Leskovec)

b/ Audience theories, design and methods

Media theory (Mc Luhan)

The phantom public (Lippmann)

Two-step flow (Katz Lazarsfeld) and influence

From panels and focus groups to social listening

c/ Psychometrics and tests

Natively digital traces, on line/ offline and mixed methods (consumer journeys).

Individual testing of cognitive activity: eye-tracking and other body sensors

Mechanical turk methods for testing

UX modeling: Subjective evaluation

5/ Collective engagement in UX (session 10 and 11)

a/ Principles

Contributions, exchanges and crowdsourcing as part of UX (comments, annotations, controversies) (boyd)

Wikipedia's political and cognitive processes (Cardon)

Distributed architectures at technical and cultural levels (Musiani)

Ecology of UX in public spaces: publics and crowds, events design.

b/ Methods

Digital Methods (Rogers and Marres)

Community management :  theory and techniques

Social Network Analysis (from reputation to multiplexed engagements) (Watts, Granovetter, Burke)

Quantified self and other communities

6/ Design methods (session 12 and 13)

a/ User modeling (from Eco to Norman)

Learn how to better differentiate (and combine) interface design, interaction design, information design

b/ User centered design (quantification and feedback data in the loop).

Testing methodologies (protocols and principles of validation)

 

Presentations and general discussion (session 14)

 

Keywords

quantification; networks; social sciences; opinion; digital architectures; digital methods; traces; memetics; attention economy; snart city.

Learning Prerequisites

Required courses

None

Recommended courses

None

Important concepts to start the course

Attention,  appropriation, public

Learning Outcomes

By the end of the course, the student must be able to:

Transversal skills

Teaching methods

Highly interactive course including readings and reports, debates, design of methods for small projects.

Expected student activities

Readings every week, documentation for case studies, debates during the sessions, small project by team of 2.

 

Assessment methods

- 40% Final Individual report in the form of an essay about one specific method (20 pages and a technical summary)

- 20% Reading report and presentation

- 40% Final Project in teams of two.

Supervision

Office hours Yes
Assistants Yes
Forum Yes

Resources

Bibliography

Benkler Yochai, The Wealth of Networks: How Social Production Transforms Markets and Freedom (Yale Press 2006).

BOULLIER, Dominique ; LOHARD, Audrey. Opinion mining et 'Sentiment analysis : Méthodes et outils. Nouvelle édition [en ligne]. Marseille : OpenEdition Press, 2012 (généré le 28 juin 2016). Disponible sur Internet : <http://books.openedition.org/oep/198>

Boullier, Dominique, Sociologie du numérique, Paris, Armand Colin, 2016.

Boullier, Dominique, Big data challenges for the social sciences: from society and opinion to replications, Working Paper, Social Media Lab EPFL, May 2016 , to be published in Big Data and Society. https://arxiv.org/abs/1607.05034

Bourdieu P. (1984). Public Opinion Does Not Exist. In A. Mattelart and S. Siegelaub (Eds.) Communication and Class Struggle. New York: International General.

Bowker G. & Leigh Star S. (1999). Sorting Things Out: Classification and its Consequences. Cambridge: MIT Press.

Bowker G. (2014). The Theory/Data Thing. Commentary, International Journal of Communication 8, 1795'1799.

Bowker Geof and Star, Susan Leigh, Sorting Things Out: Classification and Its Consequences. Geoffrey C. Bowker and Susan Leigh Star. Cambridge, MA: MIT Press, 1999. 377 pp

Boyd danah (2014). It's Complicated: The Social Lives of Networked Teens. New Haven: Yale University Press.

boyd, danah and Kate Crawford. (2012). 'Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon.' Information, Communication, & Society 15:5, p. 662-679.

Callon Michel et Bruno Latour, « Unscrewing the Big Leviathan : How Actors Macrostructure Reality and How Sociologists Help Them To Do So », in Karin D. Knorr Cetina et Aaron V. Cicourel (dir.), Advances in Social Theory and Methodology : Toward an Integration of Micro- and Macro-Sociologies, Boston, Routledge and Kegan Paul, 1981, p 277-303

Callon M., Law J., Rip A. (1986). Qualitative Scientometrics. In Callon M., Law J., Rip A., (Ed.). Mapping the Dynamics of Science and Technology. (pp.103-123), London: Macmillan,

 Cardon, Dominique, À quoi rêvent les algorithmes. Nos vies à l'heure des Big Data, Paris, Seuil, 2015

Cardon, Dominique, La démocratie internet. Promesses et limites, Paris, Seuil, 2010

Desrosières, Alain (1998). The politics of large numbers : a history of statistical reasoning. Cambridge, Mass: Harvard University Press

Didier, Emmanuel (2009) En quoi consiste l'Amérique ? Les statistiques, le New Deal et la Démocratie, Paris, La Découverte

Didier, Emmanuel, 'Sampling and Democracy: Representativeness in the First United States Surveys', Science in Context, 15 (3), pp. 427-445, 2002

Didier, Emmanuel, 2013 "Cunning observation: US Agricultural Statistics in the Time of Laissez-Faire", in History of Political Economy, HOPE Annual Supplement on Observation.

Eisenstein, E. (1983). The Printing Revolution in Early Modern Europe. Cambridge: Cambridge University Press.

John Law, Evelyn Ruppert and Mike Savage (2011), 'The Double Social Life of Methods', CRESC Working Paper 95.

Katz E. And Lazarsfeld P. (1955). Personal Influence: The Part Played by the People in the Flow of Mass Communication. Glencoe: Free Press.

Kleinberg J., D. Gibson, P. Raghavan (1998). Inferring Web Communities from Link Topology. In Proc. Of The 9th ACM Conference on Hypertext and Hypermedia (Hyper-98), (pp. 225'234), New York, June 20-24.

Kleinberg, J. (2002). Bursty and Hierarchical Structure in Streams, Proc. 8th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining.

Latour B., Jensen B., Venturini T., Grauwin S., Boullier D. (2012). The Whole Is Always Smaller Than Its Parts. A Digital Test Of Gabriel Tarde's Monads. British Journal Of Sociology, Volume 63, Issue 4, (Pp. 590'615).

Latour, Bruno (1995). The'pedofil'of Boa Vista: a photo-philosophical montage. Common Knowledge, 4 (1):144-187.

Leskovec J., L. Backstrom, J. Kleinberg (2009). Meme-Tracking and the dynamics of the news cycle. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).

 Lessig, Lawrence, Code v.2, to be downloaded at http://codev2.cc/

Mackenzie, A. and Vurdubakis, T. (2011) `Codes and codings in crisis: signification, performativity and excess', Theory, Culture & Society 28(6): 3'23.

Manovich,Lev The Science of Culture? Social Computing, Digital Humanities, and Cultural Analytics, http://manovich.net/content/04-projects/086-cultural-analytics-social-computing/cultural_analytics_article_final.pdf

Manovich,Lev, Software Takes Command, New York: Bloomsbury Academic, 2013.

Marres, N. (2007) The issues deserve more credit pragmatist contributions to the study of public involvement in controversy,  Social Studies of Science 37 (5), 759-780

Marres, N. (2015) "Why Map Issues? On Controversy as a Digital Method." Science, Technology & Human Values 40: 655-686

Marres, N. (2017) Digital Sociology, Cambridge, Polity.

 

MOROZOV, E.  (2013) To Save Everything, Click Here: Technology, Solutionism, and the Urge to Fix Problems that Don't Exist, Allen Lane.

Pentland A. (2014). Social Physics. How Good Ideas Spread. The Lessons From a New Science, Penguin Press.

Rogers, R. A. Digital Methods. Boston. MA: The MIT Press., 2013.

Ruppert, Evelyn, Law, John and Savage, Mike. (2013) Reassembling Social Science Methods: the challenge of digital devices, Theory, Culture & Society, 30(4), pp. 22-46.

Schelling Thomas C. (1971). "Dynamic Models of Segregation," Journal of Mathematical Sociology, 1(2), pp. 143'186.

Shifman, Limor, Memes in Digital Culture, MIT Press, 2014

Tarde, G. (1903) The Laws of Imitation, translated by E.C. Parsons with introduction by F.Giddings, New York, Henry, Holt and Co.

Watts D.J.  and P.S. Dodds, Influentials, networks, and public opinion formation, in Journal of Consumer Research, vol. 34, no. 4, pp. 441'458, JSTOR, 2007.

Ressources en bibliothèque
Websites
Videos

Dans les plans d'études

Semaine de référence

 LuMaMeJeVe
8-9  CM1100  
9-10    
10-11     
11-12     
12-13     
13-14 CE1100   
14-15    
15-16    
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Cours
      Exercice, TP
      Projet, autre

légende

  • Semestre d'automne
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