Making sense of digital traces: An activity theory driven ontological approach

Journal of the American Society for Information Science and Technology

Volumn 64, Issue 12, 2013, Pages 2452-2467

  Karanasios, Stan ^a   Thakker, Dhavalkumar ^a   Lau, Lydia ^a   Allen, David ^a   Dimitrova, Vania ^a   Norman, Alistair ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ILL-DEFINED DOMAINS; INTER-PERSONAL COMMUNICATIONS; MULTI-DISCIPLINARY APPROACH; ONTOLOGICAL APPROACH; ONTOLOGY DEVELOPMENT; PRIMARY CONTRIBUTION; SEMANTIC AUGMENTATIONS; USER-GENERATED CONTENT;

ACTIVITY COEFFICIENTS; C (PROGRAMMING LANGUAGE); COMMUNICATION; SEMANTICS;

ONTOLOGY;

EID: 84887429494     PISSN: 15322882     EISSN: 15322890     Source Type: Journal    
DOI: 10.1002/asi.22935     Document Type: Article

References (89)

1. Abel, F., Gao, Q., Houben, G.-J., &, Tao, K., (2011). Semantic enrichment of Twitter posts for user profile construction on the social web. Lecture Notes in Computer Science, 6643, 375-389.
2. Agichtein, E., Castillo, C., Donato, D., Gionis, A., &, Mishne, G., (2008). Finding high-quality content in social media. Proceedings of the 2008 International Conference on Web Search and Data Mining (WSDM '08) (pp. 183-194). New York: ACM.
3. Allen, D.K., Brown, A., Karanasios, S., &, Norman, A., (2013). How should technology-mediated organizational change be explained? A comparison of the contributions of critical realism and activity theory. MIS Quarterly, 37.
4. Allen, D., Karanasios, S., &, Slavova, M., (2011). Working with activity theory: Context, technology, and information behavior. Journal of the American Society for Information Science and Technology, 62 (4), 776-788. doi: 10.1002/asi.21441
5. Almeida, M.B., &, Barbosa, R.R., (2009). Ontologies in knowledge management support: A case study. Journal of the American Society for Information Science and Technology, 60 (10), 2032-2047. doi: 10.1002/asi.21120
6. Asur, S., &, Huberman, B.A., (2010). Predicting the future with social media. Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT; pp. 492-499). Toronto: IEEE Computer Society.
7. Bødker, S., (1991). Through the interface. A human activity approach to user interface design. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
8. Baader, F., &, Nutt, W., (2003). Basic description logics. In, B. Franz, C. Diego, L. M. Deborah, N. Daniele, &, F. P.-S. Peter, (Eds.), The description logic handbook (pp. 43-95). Cambridge, UK: Cambridge University Press.
9. Baker, M., (2000). The roles of models in artificial intelligence and education research: A prospective view. International Journal of Artificial Intelligence in Education, 11 (2), 122-143.
10. Bao, J., Smart, P., Braines, D., &, Shadbolt, N., (2009, June). A controlled natural language interface for semantic media wiki using the rabbit language. Paper presented at the Workshop on Controlled Natural Language (CNL '09), Marettimo Island, Italy.
11. Berners-Lee, T., Hendler, J., &, Lassila, O., (2001). The semantic web. Scientific American, 284 (5), 34-43.
12. Bizer, C., Heath, T., &, Berners-Lee, T., (2009). Linked data-The story so far. International Journal on Semantic Web and Information Systems, 5 (3), 1-22.
13. Boll, S., Jain, R., Luo, J., &, Xu, D., (2011). Introduction to special issue on social media. ACM Transactions on Multimedia Computing, Communications and Applications, 7S (1), 1-2. doi: 10.1145/2037676.2037682
14. Bollen, J., Mao, H., &, Zeng, X.-J., (2010). Twitter mood predicts the stock market. Journal of Computational Science, 2 (1), 1-8.
15. Bontcheva, K., &, Cunningham, H., (2011). Semantic annotations and retrieval: Manual, semi-automatic and automatic generation. In, J. Domingue, D. Fensel, and, J.A. Hendler, (Eds.), Handbook of semantic web technologies (pp. 77-116). Berlin: Springer.
16. Chen, H., &, Yang, C.C., (2011). Special issue on social media analytics: Understanding the pulse of the society. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 41 (5), 826-827.
17. Chen, R., Sharman, R., Rao, H.R., &, Upadhyaya, S.J., (2013). Data model development for fire related extreme events: An activity theory approach. MIS Quarterly, 37 (1), 125-147.
18. Contractor, N., (2009, February). Digital traces: An exploratorium for understanding and enabling social networks. Paper presented at the Symposium: Interdisciplinary Approaches to the Study of Large-Scale Human Networks. Annual Meeting of the American Association for the Advancement of Science (AAAS), Chicago, IL.
19. Cornelissen, J.P., (2011). Sensemaking under pressure: The influence of professional roles and social accountability on the creation of sense. Organization Science 23 (1), 118-137.
20. Cui, H., (2010). Competency evaluation of plant character ontologies against domain literature. Journal of the American Society for Information Science and Technology, 61 (6), 1144-1165. doi: 10.1002/asi.21325
21. Cui, H., (2012). CharaParser for fine-grained semantic annotation of organism morphological descriptions. Journal of the American Society for Information Science and Technology, 63 (4), 738-754. doi: 10.1002/asi.22618
22. Dadzie, A.-S., &, Rowe, M., (2011). Approaches to visualising linked data: A survey. Semantic Web, 2 (2), 89-124.
23. Denaux, R., Dolbear, C., Hart, G., Dimitrova, V., &, Cohn, A.G., (2011). Supporting domain experts to construct conceptual ontologies: A holistic approach. Journal of Web Semantics, 9 (2), 113-127.
24. Dervin, B., (1983, May). An overview of sense-making research: concepts, methods, and results to date. Paper presented at the Annual Meeting of the International Communication Association, Dallas, TX.
25. Despotakis, D., Dimitrova, V., Lau, L., Thakker, D., (2013, June). Semantic aggregation and zooming of user viewpoints in social media. Proceedings of 21st Conference on User Modeling, Adaptation and Personalization (UMAP2013), Rome, Italy. Springer LNCS.
26. Despotakis, D., Dimitrova, V., Lau, L., Thakker, D., Ascolese, A., Pannese, L., (2013, July). Views in user generated content for enriching learning environments: A semantic sensing approach. Proceedings of 16th International Conference on Artificial Intelligence in Education (AIED 2013), Memphis, TN. Springer LNCS.
27. Diplaris, S., Sonnenbichler, A., Kaczanowski, T., Mylonas, P., Scherp, A., Janik, M.,., Kompatsiaris, Y., (2011). Emerging, collective intelligence for personal, organisational and social use. In, N. Bessis, &, F. Xhafa, (Eds.), Next generation data technologies for collective computational intelligence (pp. 527-574). Berlin: Springer.
28. Edelstein, O., Factor, M., King, R., Risse, T., Salant, E., &, Taylor, P., (2011, November). Evolving Domains, problems and solutions for long term digital preservation. Paper presented at the 8th International Conference on Preservation of Digital Objects, Singapore.
29. Efron, M., (2011). Information search and retrieval in microblogs. Journal of the American Society for Information Science and Technology, 62 (6), 996-1008. doi: 10.1002/asi.21512
30. Eisenhardt, K.M., (1989). Building theories from case study research. Academy of Management Review, 14 (4), 532-550.
31. Engeström, Y., (1987). Learning by expanding: An activity-theoretical approach to developmental research. Helsinki: Orienta-Konsultit.
32. Engeström, Y., (2000). Activity theory as a framework for analyzing and redesigning work. Ergonomics, 43 (7), 960-974.
33. Fayyad, U.M., Piatetsky-Shapiro, G., &, Smyth, P., (1996). From data mining to knowledge discovery: An overview. In, U.M. Fayyad, G. Piatetsky-Shapiro, &, R. Uthurusamy, (Eds.), Advances in knowledge discovery and data mining (pp. 1-36). Menlo Park, CA: American Association for Artificial Intelligence.
34. Foot, K., (2002). Pursuing an evolving object: A case study in object formation and identification. Mind, Culture and Activity, 9 (2), 132-149.
35. Gao, H., Barbier, G., &, Goolsby, R., (2011). Harnessing the crowdsourcing power of social media for disaster relief. IEEE Intelligent Systems, 26 (3), 10-14.
36. Gayo-Avello, D., (2012). I wanted to predict elections with Twitter and all I got was this lousy paper-A balanced survey on election prediction using Twitter data. Retrieved from http://arxiv.org/abs/1204.6441
37. Gene Ontology Consortium. (2006). The Gene Ontology (GO) project in 2006. Nucleic Acids Research, 34 (Suppl 1), D322-D326.
38. Goldberg, C.B., (2003). Applicant reactions to the employment interview: A look at demographic similarity and social identity theory. Journal of Business Research, 56 (8), 561-571. doi: 10.1016/S0148-2963(01)00267-3
39. Greenberg, J., &, Méndez, E., (2009). Knitting the semantic web. London: Routledge.
40. Gruber, T.R., (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5 (2), 199-220. doi: 10.1006/knac.1993. 1008
41. Gruninger, M., &, Fox, M.S., (1994, June). The role of competency questions in enterprise engineering. Presented at the IFIP WG5.7 Workshop on Benchmarking-Theory and Practice, Trondheim, Norway.
42. Hassan Ibrahim, N., &, Allen, D., (2012). Information sharing and trust during major incidents: Findings from the oil industry. Journal of the American Society for Information Science and Technology, 63 (10), 1916-1928. doi: 10.1002/asi.22676
43. Hine, C., (2000). Virtual ethnography. London: Sage.
44. Horrocks, I., &, Sattler, U., (2005). A tableaux decision procedure for SHOIQ. Proceedings of the Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI-05, pp. 448-453). Denver, CO: Professional Book Center.
45. Kaplan, A.M., &, Haenlein, M., (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons, 53 (1), 59-68. doi: 10.1016/j.bushor.2009.09.003
46. Kaptelinin, V., (2005). The object of activity: Making sense of the sense-maker. Mind, Culture, and Activity, 12 (1), 4-18.
47. Karanasios, S., &, Allen, D.K., (2013). ICT and development in the context of Chernobyl nuclear power plant closure. Information Systems Journal, 23 (2). doi: 10.1111/isj.12011
48. Karanasios, S., Mishra, J., Allen, D., Norman, A., Thakker, D., &, Lau, L., (2011, October). Capturing real world activity: A socio-technical approach. Paper presented at the E-Challenges 2011, Florence, Italy.
49. Kim, H.H., (2005). ONTOWEB: Implementing an ontology-based web retrieval system. Journal of the American Society for Information Science and Technology, 56 (11), 1167-1176. doi: 10.1002/asi.20220
50. Kim, H.-L., Breslin, J., Kim, H.-G., &, Choi, J.-H., (2010). Social semantic cloud of tags: Semantic model for folksonomies. Knowledge Management Research & Practice, 8, 193-202.
51. Korpela, M., Mursu, A., &, Soriyan, H.A., (2002). Information systems development as an activity. Computer Supported Cooperative Work, 11, 111-128.
52. Kuhn, W., (2001). Ontologies in support of activities in geographical space. International Journal of Geographical Information Science, 15 (7), 613-631. doi: 10.1080/13658810110061180
53. Langer, R., &, Beckman, S.C., (2005). Sensitive research topics: netnography revisited. Qualitative Market Research: An International Journal, 8 (2), 189-203.
54. Lenhart, A., Purcell, K., Smith, A., &, Zickuhr, K., (2010). Social media and mobile Internet use among teens and young adults. Washington, DC: Pew Research Center.
55. Leont'ev, A.N., (1978). Activity, consciousness, and personality. Englewood Cliffs, NJ: Prentice-Hall.
56. Liang, T., -P., &, Turban, E., (2011). Introduction to the special issue: Social commerce: A research framework for social commerce. International Journal of Electronic Commerce, 16 (2), 5-13.
57. Lynch, C.F., Ashley, K.D., Aleven, V., &, Pinkwart, N., (2006). Defining "ill-defined domains": A literature survey. In, V. Aleven, K. Ashley, C. Lynch, &, N. Pinkwart, (Eds.). Proceedings of the Workshop on Intelligent Tutoring Systems for Ill-Defined Domains at the 8th International Conference on Intelligent Tutoring Systems, (pp. 1-10), Jhongli, Taiwan. Retrieved from http://hcis.in.tu-clausthal.de/pubs/2006/its/proceedings-of-the- workshop-on-intelligent-tutoring-systems-for-ill-defined-domains.pdf
58. Millar, R., &, Tracy, A., (1997). The employment interview. In, O. Hargie, (Ed.), The handbook of communication skills (2nd ed., pp. 453-479). New York: Routlege.
59. Minsky, M., (1995). Steps to artificial intelligence. In, G.F. Luger, (Ed.), Computation and intelligence, collected readings. (pp. 47-90). Menlo Park CA: MIT Press.
60. Nasukawa, T., &, Yi, J., (2003). Sentiment analysis: capturing favorability using natural language. Proceedings of the International Conference on Knowledge Capture 2003 (K-CAP '03; pp. 70-77). New York: ACM. doi: 10.1145/945645.945658
61. Nelson, M.R., &, Otnes, C.C., (2005). Exploring cross-cultural ambivalence: A netnography of intercultural wedding message boards. Journal of Business Research, 58 (1), 89-95. doi: 10.1016/s0148-2963(02)00477-0.
62. Noh, T.-G., Park, S.-B., Park, S.-Y., &, Lee, S.-J., (2010). Learning the emergent knowledge from annotated blog postings. Journal of Web Semantics: Science Services and Agents on the World Wide Web, 8 (4), 329-339.
63. O'Leary, D.E., (2010). Enterprise ontologies: Review and an activity theory approach. International Journal of Accounting Information Systems, 11 (4), 336-352. doi: 10.1016/j.accinf.2010.09.006
64. O'Leary, D.E., (2011). Blog mining-review and extensions: From each according to his opinion. Decision Support Systems, 51 (4), 821-830.
65. Page, R.E., (2012). Stories and social media: Identities and interaction. London: Routledge.
66. Parent, C., &, Spaccapietra, S., (2009). Modular ontologies. In, H. Stuckenschmidt, C. Parent, &, S. Spaccapietra, (Eds.), Modular ontologies: Concepts, theories and techniques for knowledge modularization (pp. 5-23). Berlin: Springer-Verlag.
67. Park, H.W., &, Thelwall, M., (2008). Link analysis: Hyperlink patterns and social structure on politicians' web sites in South Korea. Quality and Quantity, 42 (5), 687-697.
68. Qualman, E., (2009). Socialnomics: How social media transforms the way we live and do business. Hoboken, NJ: Wiley.
69. Rector, A.L., Zanstra, P.E., Solomon, W.D., Rogers, J.E., Baud, R., Ceusters, W.,., Wagner, J., (1998). Reconciling users' needs and formal requirements: Issues in developing a reusable ontology for medicine. IEEE Transactions on Information Technology in Biomedicine, 2 (4), 229-242.
70. Rheingold, H., (2000). The virtual community: Homesteading on the electronic frontier. Cambridge, MA: MIT Press.
71. Roth, W.-M., (2007). Emotion at work: A contribution to third-generation cultural-historical activity theory. Mind, Culture, and Activity, 14 (1), 40-63.
72. Rowe, M., Fernandez, M., Angeletou, S., &, Alani, H., (2013). Community analysis through semantic rules and role composition derivation. Journal of Web Semantics: Science Services and Agents on the World Wide Web, 18 (1), 31-47.
73. Schneider, S.M., &, Foot, K.A., (2005). Web sphere analysis: An approach to studying online action. In, C. Hine, (Ed.), Virtual methods: Issues in social research on the Internet (pp. 157-170). Oxford: Berg.
74. Stock, W.G., &, Weber, D., (2006). Facets of informetrics. Information Wissenschaft und Praxis [Information Science and Practice], 57 (8), 385-389.
75. Thakker, D., Dimitrova, V., Lau, L., Denaux, R., Karanasios, S., &, Yang-Turner, F., (2011). A priori ontology modularisation in ill-defined domains. Proceedings of I-Semantics ′11 Proceedings of the 7th International Conference on Semantic Systems (pp. 167-170). New York: ACM.
76. Thelwall, M., (2006). Interpreting social science link analysis research: A theoretical framework. Journal of the American Society for Information Science and Technology, 57 (1), 60-68.
77. Thelwall, M., &, Vaughan, L.B., &, Björneborn, L., (2005). Webometrics. Journal of the American Society for Information Science and Technology, 39 (1), 81-135.
78. Thelwall, M., Buckley, K., &, Paltoglou, G., (2011). Sentiment in Twitter events. Journal of the American Society for Information Science and Technology, 62 (2), 406-418. doi: 10.1002/asi.21462.
79. Thelwall, M., Buckley, K., &, Paltoglou, G., (2012). Sentiment strength detection for the social web. Journal of the American Society for Information Science and Technology, 63 (1), 163-173. doi: 10.1002/asi.21662
80. Thelwall, M., Sud, P., &, Vis, F., (2012). Commenting on YouTube videos: From Guatemalan rock to El Big Bang. Journal of the American Society for Information Science and Technology, 63 (3), 616-629.
81. Tsui, E., Wang, W.M., Cheung, C.F., &, Lau, A.S.M., (2010). A concept-relationship acquisition and inference approach for hierarchical taxonomy construction from tags. Information Processing and Management, 46 (1), 44-57.
82. Turkle, S., (2005). Life on the screen: Identity in the age of the Internet. New York: Simon & Schuster.
83. Uschold, M., &, Grüninger, M., (1996). Ontologies: Principles, methods, and applications. Knowledge Engineering Review, 1, 96-137.
84. von Raffler-Engel, W., (1983). The perception of nonverbal behaviour in the career interview. Amsterdam: John Benjamins Publishing Company.
85. Weick, K., (1995). Sensemaking in organizations. Thousand Oaks, CA: Sage.
86. Wells, G., (2002). The role of dialogue in activity theory. Mind, Culture, and Activity, 9 (1), 43-46.
87. West, R., &, Turner, L.H., (2011). Understanding interpersonal communication: Making choices in changing times (2nd ed.). Boston: Cengage.
88. Yi, K., (2010). A semantic similarity approach to predicting Library of Congress Subject Headings for social tags. Journal of the American Society for Information Science and Technology, 61 (8), 1658-1672.
89. Yoon, K., (2012). Conceptual syntagmatic associations in user tagging. Journal of the American Society for Information Science and Technology, 63 (5), 923-935.