Social-aware Ubiquitous Computing

CS612 & GCT671 Syllabus - Spring 2017

Prof. Dongman Lee

School of Computing / Graduate School of CT

KAIST

Overview

CS612 &GCT 671 - Social-aware Ubiquitous Computing

Instructor: Dongman Lee (dlee@kaist.ac.kr)

– Office: 803@N1

– Office Hours: 13:45 – 14:30 Mon/Wed

– Phone: 42-350-3559 (Office)

Class Hours: 10:30-11:45 on Mon/Wed

Classroom: 3444 @ E3-1

Language: English

Assistant: CS – H. Park; GCT – D. Chang

mailto:dlee@kaist.ac.kr

Course Description

This course introduces the fundamentals of social aware

ubiquitous computing.

The first half of the course focuses on the main components

of social aware ubiquitous computing. The core concepts

will be explained by analysis of and discussion on existing

approaches.

Applied subjects like urban computing, spontaneous service

computing, and mobile social software will be delth in the

second half. During this part, students will be asked to

participate in reading key papers and presenting them

during the class.

Students are asked to prototype a social aware ubiquitous

computing application and/or system as a term project.

Objectives

Through this class, students will learn the concept and

issues of the social aware ubiquitous computing, the

evolutionary change of urban spaces and spontaneous

interactions in a urban life in a new collective way.

Students will be introduced the followings:

– The main concept and major research topics of the ubiquitous

computing

– Research topics and key trends of social networks and media

– New applications and services oriented to social aware ubiquitous

computing

– New platforms for building applications/systems based on social

aware ubiquitous computing environments

Text and References

No textbook. Professors will prepare the presentation

materials and be distributed by assistants. According to

each topic, references will be given for further reading.

Books to understand the perspectives of strategic thinkers

and scholars will be introduced

Other materials such as news articles, market research

reports, famous bloggers posts will be used during

discussions

General References

Keith Evan Geree. Architectural Robotics. MIT Press, 2016.

Malcolm McCullough. Ambient Commons. MIT Press, 2013.

Matthew Carmona et al. Public Places Urban Spaces, Architeural Press,

2003.

N. Christakis and J. Fowler. Connected: The Surprising Power of Our

Social Networks and How They Shape Our Lives. Little, Brown and

Company, Sept. 2009

Duncan Watts. Six degrees: The science of a connected age. W.W.

Norton & Company, Feb. 2004

S. Wasserman and K. Faust. Social Network Analysis: Methods and

Applications. Cambridge University Press, Cambridge (1994)

Gavin Bell. Building Social Web Applications. O’Reilly 2009

John L. Martin. Social Structure. Princeton University Press 2009

Prerequisites and Evaluation

Prerequisites:

– Experiences in developing applications with large-scale of data

– Students from CS

• Two of Computer Networks, Operating Systems, or Computer

Architecture

• Fluency in Java or C++

– Students from GSCT

• Introduction to Social Computing (GCT673)

• CT Project (GCT503)

Grading Policy

– Midterm Exam (20%), Final Exam (20%)

– Term Paper/Project (25%)

– Presentation & Participation (35%)

Course Topics

Week 1-2: Social-Aware Ubiquitous Computing - Overview

– Evolution of Computing

– Vision and definition of Ubiquitous Computing

• M. Weiser, “The Computer for the 21st Century,” Scientific American, vol. 265,

no. 3, pp. 94–101, Sept. 1991. (available at:

http://www.ubiq.com/hypertext/weiser/SciAmDraft3.html) *

• M. Satyanarayanan, “Pervasive Computing: Vision and Challenges,” IEEE

Personal Communications, vol. 8, no. 4, pp. 10–17, Aug. 2001.

• J. Thom-Santelli, “Mobile Social Software: Facilitating Serendipity or Encouraging

Homogeneity?, IEEE Pervasive Computing, vol. 6, no. 3, pp. 46-51, Jul-Sep.

2007.

• M.N. Ko et al., “Social Networks Connect Services,” IEEE Computer,pp.37-43,

Aug. 2010.

• P. Lukowicz, A. Pentland, and A. Ferscha, “From Context Awareness to Social

Aware Computing,” IEEE Pervasive Computing, Vol. 8, No.1, pp. 32-40, Jan-Mar,

2012

• P. Barnaghi et al, “Physical-Cyber-Social Computing: Loking Back, Looking

Forward,” IEEE Internet Computing, pp.7-11, May/June 2015. *

Course Topics

Week 3: Enviornment Sensing

– How to get information from the surroundings

– Sensors in ubiquitous computing: movement, light, proximity,…

– Location sensing

• A. Ranganathan, J. Al-Muhtadi, S. Chetan, R. Campbell, and M. D. Mickunas,

“MiddleWhere: A Middleware for Location Awareness in Ubiquitou Computing

Applications,” in Proceedings of the 5th ACM/IFIP/USENIX International

Conference on Middleware, 2004, pp. 397–416.

• G. Borriello, M. Chalmers, A. LaMarca, and P. Nixon, “Delivering REAL-WORLD

Ubiquitous Location Systems,” Communications of the ACM, vol. 48, no. 3, pp.

36–41, Mar. 2005.

• S. Vihavainen, A. Oulasvirta, and R. Sarvas, “‘I can't lie anymore!’: The

implications of location automation for mobile social applications,” in MobiQuitous

'09. pp.1-10, 13-16 July 2009

• T. Teixerira, G. Dublon, and A. Savvides, “A survey of human-sensing: methods

for detecting presence, count, location, track, and identity,” ENALAB Tech Report,

09-2010, Vol. 1, No. 1, Sep. 2010 *

Course Topics

Week 4: Context Awareness

– Context Representation: What, Where, When, Who, How

– Management of context information to support users’ tasks

– Context-aware decision engines

• G. D. Abowd, A. K. Dey, P. J. Brown, N. Davies, M. Smith, and P. Steggles,

“Towards a better understanding of context and context-awareness,” 1st

international symposium on Handheld and Ubiquitous Computing, pp. 304–307,

1999.

• K. Henricksen, J. Indulska, "Developing Context-aware Pervasive Computing

Applications: Models and Approach," Journal of Pervasive and Mobile Computing,

vol. 2, no. 1, pp. 37-64, 2006.

• K. Rehman, F. Stajano, and G. Coulouris, "An Architecture for Interactive

Context-Aware Applications," IEEE Pervasive Computing Magazine, vol. 6, no. 1,

pp. 73-80, 2007

• C. Perera, A. Xaslavsky, P. Christen, and D. Georgakopoulos, “Context-Aware

Computing for The Internet of Things: A Survey,” IEEE Communications Survey &

Tutorials, Vol. 16, No. 1, pp. 414-454, 1Q 2014. *

• X. Li, M. Eckert, J. Martinez, and G. Rubio, “Contex Aware Middleware

Architecture: Survey and Challenges,” Sensors 2015, 15, 20570-20607.

Course Topics

Week 5: Service Discovery

– Adapt to changes in the environment

– Dynamically add new services/elements that enhance users’

experiences

• S. Ou, K. Yang and Q. Zhang, An efficient runtime offloading approach for

pervasive services. Wireless Communications and Networking Conference, 2006.

WCNC 2006. IEEE, 4:2229–2234, 2006.

• N.A. Nordin, W.H. Shin, K.I. Bin Ghauth and M.I. Bin Mohd Tamrin, “Using

service-based content adaptation platform to enhance mobile user experience”, In

Mobility '07. 552-557. 2007

• S.B. Mokhtar, D. Preuveneers, N. Georgantas, V. Issarny, and Y. Berbers ,

“EASY: Efficient semAntic Service discoverY in pervasive computing

environments with QoS and context support”, The Journal of Systems and

Software, vol. 81, n. 5, pp. 785-808, 2008

• Michael Rambold, Holger Kasinger, Florian Lautenbacher and Bernhard Bauer,

“Towards Autonomic Service Discovery – A Survey and Comparison,” IEEE Int’l

Conference on Service Computing, pp. 192-201, 2009. *

Course Topics

Week 6: Spontaneous Interaction Theories – BERGER, C. R. and CALABRESE, R. J. (1975). SOME EXPLORATIONS IN INITIAL

INTERACTION AND BEYOND: TOWARD A DEVELOPMENTAL THEORY OF INTERPERSONAL COMMUNICATION. Human Communication Research, vol. 1, no. 2, pp. 99–112. *

– SYKES, R. E. (1983). INITIAL INTERACTION BETWEEN STRANGERS AND ACQUAINTANCES A Multivariate Analysis of Factors Affecting Choice of Communication Partners. Human Communication Research, vol. 10, no. 1, pp. 27–53.

– DOUGLAS, W. (1991). Expectations About Initial Interaction An Examination of the Effects of Global Uncertainty. Human Communication Research, vol. 17, no. 3, pp. 355–384.

– Tidwell, N. D., Eastwick, P. W., and Finkel, E. J. (2013). Perceived, not actual, similarity predicts initial attraction in a live romantic context: Evidence from the speed-dating paradigm. Personal Relationships, vol. 20, no. 2, pp. 199–215.

– Dryer, D. C. and Horowitz, L. M. (1997). When do opposites attract? Interpersonal complementarity versus similarity. Journal of Personality and Social Psychology, vol. 72, no. 3, pp. 592–603.

– Lee, A. Y. (2001). The mere exposure effect: An uncertainty reduction explanation revisited. Personality and Social Psychology Bulletin, vol. 27, no. 10, pp. 1255–1266.

– Paulos, E. and Goodman, E. (2004). The familiar stranger: anxiety, comfort, and play in public places. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’04) (vol. 6, pp. 223–230). New York, New York, USA: ACM Press.

Course Topics

Week 7: Mobile Social Software I – Mao, Z., Jiang, Y., Min, G., Leng, S., Jin, X., and Yang, K. (2016). Mobile social networks:

Design requirements, architecture, and state-of-the-art technology. Computer Communications.

– Jabeur, N., Zeadally, S., and Sayed, B. (2013). Mobile Social Networking Applications. Commun. ACM, vol. 56, no. 3, pp. 71–79.

– Navarro, N. D. A. B., Costa, C. A. Da, Barbosa, J. L. V., and Righi, R. D. R. (2016). A context-aware spontaneous mobile social network. UIC-ATC-ScalCom-CBDCom-IoP 2015 (pp. 85–92).

– Champion, A. C., Yang, Z., Zhang, B., Dai, J., Xuan, D., and Li, D. (2013). E-SmallTalker: A distributed mobile system for social networking in physical proximity. IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 8, pp. 1535–1545.

– Guo, B., Zhang, D., Yu, Z., Zhou, X., and Zhou, Z. (2012). Enhancing spontaneous interaction in opportunistic mobile social networks. Communications in Mobile Computing, vol. 1, no. 1, pp. 6.

– Wei, P.-S. and Lu, H.-P. (2014). Why do people play mobile social games? An examination of network externalities and of uses and gratifications. Internet Research, vol. 24, no. 3, pp. 3.

– Hsiao, J. C.-Y. and Dillahunt, T. R. (2017). People-Nearby Applications: How Newcomers Move Their Relationships Offline and Develop Social and Cultural Capital. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW ’17 (pp. 26–40). New York, New York, USA: ACM Press.

– Terveen, L. and McDonald, D. W. (2005). Social matching: A framework and research agenda. ACM Transactions on Computer-Human Interaction, vol. 12, no. 3, pp. 401–434.

Course Topics

Week 8: Midterm exam

Course Topics

Week 9: Mobile Social Software II – Ma, X. (2017). What Happens in happn: The Warranting Powers of Location History in Online

Dating. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW ’17 (pp. 41–50). New York, New York, USA: ACM Press.

– Blackwell, C., Birnholtz, J., and Abbott, C. (2014). Seeing and being seen: Co-situation and impression formation using Grindr, a location-aware gay dating app. New Media & Society, pp. 1461444814521595-.

– Camacho, T., Foth, M., and Rakotonirainy, A. (2013). TrainRoulette: promoting situated in-train social interaction between passengers. In Adjunct Proceedings of the 2013 International Joint Conference on Pervasive and Ubiquitous Computing (vol. 2, pp. 1385–1388).

– Morán, A. L., Rodríguez-Covili, J., Mejia, D., Favela, J., and Ochoa, S. (2010). Supporting informal interaction in a hospital through impromptu social networking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (vol. 6257 LNCS, pp. 305–320).

– Chen, J. and Abouzied, A. (2016). One LED is Enough : Catalyzing Face-to-face Interactions at Conferences with a Gentle Nudge. Proc. 19th ACM Conf. on Computer-Supported Cooperative Work & Social Computing, pp. 172–183.

– Brown, C., Efstratiou, C., Leontiadis, I., Quercia, D., and Mascolo, C. (2014). Tracking serendipitous interactions. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing - CSCW ’14 (pp. 1072–1081). New York, New York, USA: ACM Press.

– Raban, D. R., Ricken, S. T., Grandhi, S. A., Laws, N., and Jones, Q. (2009). Hello stranger! A study of introductory communication structure and social match success. In Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS.

– Memarovic, N., Elhart, I., and Rubegni, E. (2016). “Fun place within a serious space: stimulating community interaction and engagement through situated snapshots in a university setting.” In Proceedings of the 15th International Conference on Mobile and Ubiquitous Multimedia - MUM ’16 (pp. 11–23). New York, New York, USA: ACM Press.

Course Topics

Week 10: Placeness (or ”Sense of place”) – Philosophy: T. Cresswell. Place. 2009. Royal Holloway, University of

London, Egham, UK

– Architecture: Hashem, H., Seyed Abbas, Y., Ali Akbar, H., & Nazgol, B.

(2013). Comparison the concepts of sense of place and attachment to place

in Architectural Studies. Geografia: Malaysian Journal of Society and Space,

9(1), 107-117.

– Social science: J.E. Cross. What is Sense of Place. 2001. Department of

Sociology, Colorado State University

– CSCW: Dourish, P. (2006, November). Re-space-ing place: place and space

ten years on. In Proceedings of the 2006 20th anniversary conference on

Computer supported cooperative work (pp. 299-308). ACM.

– Ubiquitous computing: Agre, P. E. (2001). Changing places: contexts of

awareness in computing. Human-computer interaction, 16(2), 177-192.

Location-based service: Farrelly, G. (2014). Irreplaceable: the role of place

information in a location based service. Journal of Location Based Services,

8(2), 123-132.

Course Topics

Week 11: Urban computing (Extracting place semantics) – Adams, B., & McKenzie, G. (2013). Inferring thematic places from

spatially referenced natural language descriptions. In Crowdsourcing

geographic knowledge (pp. 201-221). Springer Netherlands.

– Kang, J. H., Welbourne, W., Stewart, B., & Borriello, G. (2004, October).

Extracting places from traces of locations. In Proceedings of the 2nd

ACM international workshop on Wireless mobile applications and services

on WLAN hotspots (pp. 110-118). ACM.

– Lv, M., Chen, L., Xu, Z., Li, Y., & Chen, G. (2016). The discovery of

personally semantic places based on trajectory data mining.

Neurocomputing, 173, 1142-1153.

– Kim, E., Ihm, H., & Myaeng, S. H. (2014, April). Topic-based place

semantics discovered from microblogging text messages. In

Proceedings of the 23rd International Conference on World Wide Web (pp.

561-562). ACM.

– Lee, R., Wakamiya, S., & Sumiya, K. (2013). Urban area characterization

based on crowd behavioral lifelogs over Twitter. Personal and ubiquitous

computing, 17(4), 605-620.

Course Topics

Week 11: Urban computing (Extracting place semantics) – Hiruta, S., Yonezawa, T., Jurmu, M., & Tokuda, H. (2012, September).

Detection, classification and visualization of place-triggered geotagged

tweets. In Proceedings of the 2012 ACM Conference on Ubiquitous

Computing (pp. 956-963). ACM.

– Dearman, D., & Truong, K. N. (2010, September). Identifying the activities

supported by locations with community-authored content. In

Proceedings of the 12th ACM international conference on Ubiquitous

computing (pp. 23-32). ACM.

– Cranshaw, J., Toch, E., Hong, J., Kittur, A., & Sadeh, N. (2010, September).

Bridging the gap between physical location and online social networks.

In Proceedings of the 12th ACM international conference on Ubiquitous

computing (pp. 119-128). ACM.

– Chon, Y., Lane, N. D., Li, F., Cha, H., & Zhao, F. (2012, September).

Automatically characterizing places with opportunistic crowdsensing

using smartphones. In Proceedings of the 2012 ACM Conference on

Ubiquitous Computing (pp. 481-490). ACM.

–

Course Topics

Week 12: Urban computing (Levering placeness for urban

smart applications)

– Kim, D. H., Han, K., & Estrin, D. (2011, September). Employing

user feedback for semantic location services. In Proceedings of

the 13th international conference on Ubiquitous computing (pp. 217-

226). ACM.

– Leggieri, M., von der Weth, C., & Breslin, J. G. (2015, April). Using

sensors to bridge the gap between real places and their web-

based representations. In Intelligent Sensors, Sensor Networks

and Information Processing (ISSNIP), 2015 IEEE Tenth International

Conference on (pp. 1-6). IEEE.

– Yang, D., Zhang, D., Yu, Z., & Yu, Z. (2013, September). Fine-

grained preference-aware location search leveraging

crowdsourced digital footprints from LBSNs. In Proceedings of

the 2013 ACM international joint conference on Pervasive and

ubiquitous computing (pp. 479-488). ACM.

Course Topics

Week 13: Urban computing (Levering placeness for urban

smart applications)

– Matic, A., Osmani, V., & Mayora-Ibarra, O. (2014, September).

Mobile monitoring of formal and informal social interactions at

workplace. In Proceedings of the 2014 ACM International Joint

Conference on Pervasive and Ubiquitous Computing: Adjunct

Publication (pp. 1035-1044). ACM.

– Krumm, J., & Rouhana, D. (2013, September). Placer: semantic

place labels from diary data. In Proceedings of the 2013 ACM

international joint conference on Pervasive and ubiquitous computing

(pp. 163-172). ACM.

– Srinivasan, V., Moghaddam, S., Mukherji, A., Rachuri, K. K., Xu, C.,

& Tapia, E. M. (2014, September). Mobileminer: Mining your

frequent patterns on your phone. In Proceedings of the 2014 ACM

International Joint Conference on Pervasive and Ubiquitous

Computing (pp. 389-400). ACM.

Course Topics

Week 14: Term Project Presentation

Course Topics

Week 15: Final exam