Billedindeksering og sociale medier

  • Susanne Ørnager Institut for kommunikation, Københavns Universitet
  • Haakon Lund Institut for kommunikation, Københavns Universitet
Nøgleord: Billedindeksering, sociale medier, billedgenfinding, fotografier, billedfacetter, litteraturanalyse af billeder, PRISMA Grounded Theory, citationsanalyse af billeder, billedbehandling, tekstgenkendelse, billedalgoritmer

Resumé

This article focuses on the methodologies, organization, and communication of digital image collection research that utilizes social media content. “Image” is here understood as a cultural, conventional, and commercial—stock photo—representation. Two methodologies i.e. PRISMA and Grounded Theory are employed to examine, categorize and analyze images and comprehend how humans consider them. The literature review covers research since 2005, when major social media platforms emerged. It demonstrates that the images on social media have not changed the overall direction of research into image indexing and retrieval, though new topics on crowdsourcing and tagging have emerged in it. A citation analysis includes an overview of co-citation maps that demonstrate the nexus of image research literature and the journals in which they appear. The results point to new possibilities influencing the research by providing large image collections as new testbeds for improving or testing research hypothesis on a new scale.

Referencer

Albertson, D. (2015). Visual information seeking. Journal of the American Society for Information Science and Technology, 66(6), 1091–1105. DOI: 10.1002/asi.23244
Ames, M. and Naaman, M. (2007). Why we tag: Motivations for annotation in mobile and online media. CHI 2007, April 28–May 3, 2007, San Jose, CA, 1–10. DOI: 10.1145/1240624.1240772
Andre, P., Cutrell, E., Tan, D. S., and Smith, G. (2009). Designing novel image search interfaces by understanding unique characteristics and usage. In Gross, T. et al. (Eds.). Human-Computer Interaction – INTERACT 2009, 340–353. Lecture Notes in Computer Science, vol. 5727. Springer, Berlin, Heidelberg. DOI: 10.1007/9783642036583_40
Angus, E., Stuart, D., and Thelwall, M. (2010). Flickr’s potential as an academic image resource: An exploratory study. Journal of Librarianship and Information Science, 42(4), 268–278. DOI: 10.1177/0961000610384656
Barthes, R. (1964). Rhetoric of the Image. In Heath, S. (Ed.) Roland Barthes: Image – Music – Text, London: Fontana Press, 1977. Originally published as “Rhetorique de l’image” in Communications 4: 40–51. DOI: 10.1007/978-1-349-03518-2
Beaudoin, J. E. (2012). Context and its role in the digital preservation of cultural objects. D-Lib Magazine, 18(11/12). DOI: 10.1045/november2012-beaudoin1
Beaudoin, J. E. (2014). A framework of image use among archaeologists, architects, art historians and artists. Journal of Documentation, 70(1), 119–147. DOI: 10.1108/JD-12-2012-0157
Beaudoin, J. E. (2015). Content-based image retrieval methods and professional image users. Journal of the American Society for Information Science and Technology, 67(2), 350–365, 2016.
Beaudoin, J. E. (2016). Describing images: A case study of visual literacy among library and information science students. College & Research Libraries, 77(3), 376–392. DOI: 10.5860/crl.77.3.376
Benson, A. C. (2015). Image descriptions and their relational expressions: a review of the literature and the issues. Journal of Documentation, 71(1), 143–164. DOI: 10.1108/JD-07-2013-0093
Chen, H., Kochtanek, T., Burns, C. S., and Shaw, R. (2010). Analyzing users’ retrieval behaviors and image queries of a photojournalism image database. The Canadian Journal of Information and Library Science, 34(3), 249–270. DOI: 10.1353/ils.2010.0003
Choi, Y. (2013). Analysis of image search queries on the web: Query modification patterns and semantic attributes. Journal of the American Society for Information Science and Technology, 64(7), 1423–1441. DOI: 10.1002/asi.22831
Choi, Y. and Hsieh-Yee, I. (2010). Finding images in an online public access catalogue: Analysis of user queries, subject headings, and description notes. The Canadian Journal of Information and Library Science 34(3), 271–298. DOI: 10.1353/ils.2010.0004
Choi, Y. and Rasmussen, E. M. (2003). Searching for images: The analysis of users’ queries for image retrieval in American history. Journal of the Association for Information Science and Technology, 54(6), 498–511. DOI: 10.1002/asi.10237
Christensen, H. D. (2017). Rethinking image indexing? Journal of the Association for Information Science and Technology, 68(7), 1782–1785. DOI: 10.1002/asi.23812
Chu, H. T. (2001). Research in image indexing and retrieval as reflected in the literature. Journal of the American Society for Information Science and Technology. 52(12), 1011-1018.
Chung, E. K. and Yoon, J. W. (2009). Categorical and specificity differences between user-supplied tags and search query terms for images. An analysis of Flickr tags and Web image search queries. Information Research, 14(3).
Chung, E. K. and Yoon, J. W. (2011). Image needs in the context of image use: An exploratory study. Journal of Information Science, 37(2), 163–177. DOI: 10.1177/0165551511400951
Conduit, N. and Rafferty, P. (2007). Constructing an image indexing template for The Children’s Society. Users’ queries and archivists’ practice. Journal of Documentation, 63(6), 898–919. DOI: 10.1108/00220410710836411
Drew, S. and Guillemin, M. (2014). From photographs to findings: visual meaning-making and interpretive engagement in the analysis of participant generated images. Visual Studies, 29(1), 54–67. DOI: 10.1080/1472586X.2014.862994
Enser, P. (2000). Visual image retrieval: seeking the alliance of concept-based and content-based paradigms. Journal of Information Science, 26(4), 199–210. DOI: 10.1177/0165551004233212.
Enser, P. G. B., Sandom, C. J., and Lewis, P. H. (2005). Automatic annotation of images from the practitioner perspective. In Leow, W.-K. et al. (Eds.), CIVR 2005, LNCS 3568, 497–506. DOI: 10.1007/11526346_53
Enser, P. G. B., Sandom, C. J., Hare, J. S., and Lewis, P. H. (2007). Facing the reality of semantic imageretrieval. Journal of Documentation, 63(4), 465–481. DOI: 10.1108/00220410710758977
Estelle´s-Arolas, E. and Gonza´lez-Ladro´n-de-Guevara, F. (2012). Toward an integrated crowdsourcing definition. Journal of Information Science 38(2), 189–200. DOI: 10.1177/0165551512437638
Fauzi, F. and Belkhatir, M. (2013). Multifaceted conceptual image indexing on the world wide web. Information Processing and Management 49, 420–440. DOI: 10.1016/j.ipm.2012.08.001
Fauzi, F. and Belkhatir, M. (2014). Image understanding and the web: a state-of-the-art Review. Journal of Intelligent Information Systems, 43, 271–306. DOI: 10.1007/s10844-014-0323-6
Fei-Fei, L. (2016). How we teach computers to understand pictures. TED Talk. Lokaliseret 7-12-2018 på: https://www.youtube.com/watch?v=40riCqvRoMs
Glaser, B. (1992). Basics of Grounded Theory Analysis. Mill Valley, CA: Sociology Press.
Glaser, B. and Strauss, A. (1967). The Discovery of Grounded Theory. Chicago: Aldine.
Goker, A., Butterworth, R., MacFarlane. A., Ahmed, T. S., and Stumpf, S. (2016). Expeditions through image jungles. Journal of Documentation, 72(1), 5–23, DOI: 10.1108/JD-01-2014-0019
Hajibayova, L. (2013). Basic-level categories: A review. Journal of Information Science, 39(5) 676–687. DOI: 10.1177/0165551513481443
Huang, H. and Jorgensen, C. (2013). Characterizing user tagging and co-occurring metadata in general and specialized metadata collections. Journal of the American Society for Information Science and Technology, 64(9), 1878–1889. DOI: 10.1002/asi.22891
Hung, T. Y. (2012). An analysis of photo editors’ query formulations for image retrieval. Journal of Librarianship and Information Studies, 4(1), 13–16.
Informationsordbogen (2018). Det Informationsvidenskabelige Akademi. Københavns Universitet.
Jansen, B. J. (2008). Searching for digital images on the web. Journal of Documentation, 64(1), 81 –101. Permanent link to this document: http://dx.doi.org/10.1108/00220410810844169
Jörgensen, C. (1995). Image attributes: An investigation (Indexing systems, retrieval systems, computerized). Unpublished doctoral dissertation, Syracuse University, NY.
Jörgensen, C. (1998). Attributes of images in describing tasks. Information Processing and Management, 34(2/3), 161-174
Jörgensen, C. (2003). Image retrieval: theory and research. The Scarecrow Press, Lanham, MA and Oxford.
Jörgensen, C. (2007). Image access, the semantic gap, and social tagging as a paradigm shift. 18th Annual ASIS SIG/CR Classification Research Workshop, 1-9, DOI: 10.7152/acro.v18i1.12868
Jörgensen, C. (2010). Still image indexing. Encyclopedia of Library and Information Sciences. 3rd ed. DOI: 10.1081/E-ELIS3-120044380
Jörgensen, C. and Jörgensen, P. (2005). Image querying by image professionals. Journal of the American Society for Information Science and Technology, 56(12), 1346–1359. https://doi.org/10.1002/asi.20229
Jörgensen, C., Stvilia, B., and Wu, S. (2013). Assessing the relationships among tag syntax, semantics, and perceived usefulness. Journal of the American Society for Information Science and Technology, 65(4), 836–849, 2014.
Klenczon, W. and Rygiel, P. (2014). Librarian cornered by images, or how to index visual resources. Cataloging & Classification Quarterly, 52(1), 42–61. DOI: 10.1080/01639374.2013.848123
Konkova, E., Goker, A.S., Butterworth, R., & MacFarlane, A. (2014). Social Tagging: Exploring the Image, the Tags, and the Game. Knowledge Organization, 41(1), 57-65.
Kovacs, B. L. and Takacs, M. (2014). New search method in digital library image collections: A theoretical inquiry. Journal of Librarianship and Information Science, 46(3), 217–225. DOI: 10.1177/0961000614526611
Konkova, E., MacFarlane, A., and Goker, A. (2016). Analysing creative image search information needs. Knowledge Organization, 43(1).
Layne, S. S. (1994). Some issues in the indexing of images. Journal of the American Society for Information Science, 4(8), 583–588.
Lee, H. J. and Neal, D. (2010). A new model for semantic photograph description combining basic levels and user-assigned descriptors. Journal of Information Science, 36(5), 547–565. DOI: 10.1177/0165551510374930
Lin, Y. L., Trattner, C., Brusilovsky, P., and He, D. (2015). The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags. Journal of the American Society for Information Science and Technology, 66(9), 1785–1798. DOI: 10.1002/asi.23292
Maniu, S., O’Hare, N., Aiello, L. M., Chiarandini, L., and Jaimes, A. (2013). Search behavior on photo sharing platforms, presented at IEEE International Conference on Multimedia and Expo (ICME), July 15–19, 2013, San Jose, CA. DOI: 10.1109/ICME.2013.6607496
Matusiak, K. K. (2013). Image and multimedia resources in an academic environment: A qualitative study of students’ experiences and literacy practices. Journal of the American Society for Information Science and Technology, 64(8), 1577–1589. DOI: 10.1002/asi.22870
Moher, D., Liberati, A., Tetzlaff, J., and Altman, D.G. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement, Annals of Internal Medicine, 151(4), 264–269.
Mounika, B., Sowmya, Y., Pasala, S., and Sravani, A. (2016). Content-based image retrieval using color. International Journal of Applied Engineering Research, 11(6), 4331–4334.
Nakatsu, R. T., Grossman, E. B., and Iacovou, C. L. (2014). A taxonomy of crowdsourcing based on task complexity. Journal of Librarianship and Information Science, 40(6), 823–834. DOI: 10.1177/0165551514550140
Nations, D. (2017). What Is Social Media? Explaining the Big Trend.
Neal, D. (2008). News photographers, librarians, tags, and controlled vocabularies: Balancing the forces. Journal of Library Metadata, 8(3), 199–219. DOI: 10.1080/19386380802373936
Neal, D. (2010). Emotion-based tags in photographic documents: The interplay of text, image, and social influence. The Canadian Journal of Information and Library Science 34(3), 329-353. DOI: 10.1353/ils.2010.0000
Nov, O. and Ye, C. (2010). Why do people tag? Motivations for photo tagging. Communications of the ACM, 53(7), 128-131. DOI: 10.1145/1785414.1785450
Obar, J. and Wildman, S. (2015). Social media definition and the governance challenge: An introduction to the special issue. Telecommunications Policy, 39(9), 745–750. DOI: 10.1016/j.telpol.2015.07.014
Ornager, S. (1997). Image retrieval: Theoretical analysis and empirical user studies on accessing information in images. Proceedings of the American Society for Information Science Annual Meeting 34: 202–11.
Panofsky, E. (1962). Studies in Iconology: Humanistic Themes in the Art of Renaissance. Reprinted, New York: Harper and Row.
Park, J. Y., O’Hare, N., Schifanella, R., Jaimes, A., and Chung, C. W. (2015). A large-scale study of user image search behavior on the Web. Presented at CHI 2015, Crossings, April 18–23, 2015, Seoul, Korea, 985–994. DOI: 10.1145/2702123.2702527
Petek, M. (2012). Comparing user-generated and librarian-generated metadata on digital images. OCLC Systems & Services: International Digital Library Perspectives, 28(2), 101–111. DOI: 10.1108/10650751211236659
Peters, I. and Stock, W. G. (2010). Power tags in information retrieval, Library Hi Tech, 28(1), 81– 93. Permanent link to this document: http://dx.doi.org/10.1108/07378831011026706
Piras, L. and Giacinto, G. (2017). Information fusion in content based image retrieval: A comprehensive overview. Information Fusion, 37, 50–60. DOI: 10.1016/j.inffus.2017.01.003
Rafferty, P. and Albinfalah, F. (2014). A tale of two images: the quest to create a story-based image indexing system. Journal of Documentation, 70(4), 605-621. DOI: 10.1108/JD-10-2012-0130
Rafferty, P. and Hidderley, R. (2007). Flickr and democratic indexing: Dialogic approaches to indexing. Aslib Proceedings: New Information Perspectives, 59(4/5), 397–410. DOI: 10.1108/00012530710817591
Ransom, N. and Rafferty, P. (2011). Facets of user-assigned tags and their effectiveness in image retrieval. Journal of Documentation, 67(6), 1038–1066. http://dx.doi.org/10.1108/00220411111183582
Reilly, M. and Thompson, S. (2014). Understanding ultimate use data and its implication for digital library management: A Case Study. Journal of Web Librarianship, 8(2), 196-213. DOI: 10.1080/19322909.2014.901211
Ren, M., Kiros, R., and Zemel, R.S. (2015). Exploring models and data for image question answering. In proceedings Advances in neural information processing systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7–12, Montreal, Qubec, Canada, 2953–2961.
Rorissa, A. (2008). User-generated descriptions of individual images versus labels of groups of images: A comparison using basic level theory. Information Processing and Management 44, 1741–1753.
Rorissa, A. (2010). A Comparative Study of Flickr Tags and Index Terms in a General Image Collection. Journal of the American Society for Information Science and Technology, 61(11), 2230–2242
Rorissa, A., & Iyer, H. (2008). Theories of Cognition and Image Categorization: What Category Labels Reveal About Basic Level Theory. Journal of the American Society for Information Science and Technology, 59(7), 1–10.
Rorissa, A., Clough, P., & Deselaers, T. (2008). Exploring the Relationship Between Feature and Perceptual Visual Spaces. Journal of the American Society for Information Science and Technology, 59(5), 770-784.
Rosch, E., Mervis, C. B., Gray, W., Johnson, D., and Boyes-Braem, P. (1976). Basic objects in natural categories. Cognitive Psychology, 8(3), 382–439. DOI: 10.1016/0010-0285(76)90013-X
Rüger, S. (2011). Multimedia resource discovery. In: Melucci M., Baeza-Yates R. (eds) Advanced Topics in Information Retrieval. 157–186. The Information Retrieval Series, vol 33. Berlin, Heidelberg: Springer
Savage, N. (2016). Seeing more clearly. Communications of the ACM, 59(1), 20–22. DOI: 10.1145/2843532
Schmidt, S. and Stock, W. G. (2009). Collective indexing of emotions in images. A study in emotional information retrieval. Journal of the American Society for Information Science and Technology, 60(5), 863–876. DOI: 10.1002/asi.21043
Shatford, S. (1986). Analyzing the subject of a picture: A theoretical approach. Cataloguing and Classification Quaterly, 6(3), 39–62. DOI: 10.1300/J104v06n03_04
Springer, M., Dulabahn, B., Michel, P., Natanson, B., Reser, D., Woodward, D., and Zinkham, H. (2008). For the Common Good: The Library of Congress Flickr Pilot Project. Library of Congress, Washington.
Springer, M., Dulabahn, B., Michel, P., Natanson, B., Reser, D., Woodward, D., and Zinkham, H. (2008). For the Common Good: The Library of Congress Flickr Pilot Project. Washington: Library of Congress
Stewart, B. (2010). Getting the picture: An exploratory study of current indexing practices in providing subject access to historic photographs. The Canadian Journal of Information and Library Science 34(3), 297–327. DOI: 10.1353/ils.2010.0005
Stvilia, B. and Jorgensen, C. (2009). User-generated collection-level metadata in an online photo-sharing system. Library & Information Science Research, 31, 54–65. DOI: 10.1016/j.lisr.2008.06.006
Stvilia, B. and Jorgensen, C. (2010). Member activities and quality of tags in a collection of historical photographs in Flickr. Journal of the American Society for Information Science and Technology, 61(12), 2477–2489. DOI: 10.1002/asi.21432
Stvilia, B., Jorgensen, C., and Wu, S. (2012). Establishing the value of socially-created metadata to image indexing. Library & Information Science Research, 34, 99–109. DOI: 10.1016/j.lisr.2011.07.011
Strauss, A. and Corbin, J. (1990). Basics of Qualitative Research. Grounded Theory Procedures and Techniques. Newbury Park, CA: Sage.
Strauss, A. and Corbin, J. (1998). Basics of Qualitative Research Techniques and Procedures for Developing Grounded Theory, (2nd ed.). Sage Publications: London.
Tang, L. and Carter, J. A. (2011). Communicating image content. Proceedings of the Human Factors and Ergonomics Society 55th Annual Meeting. DOI: 10.1177/1071181311551102
Terras, M. (2011). The digital wunderkammer: Flickr as a platform for amateur cultural and heritage content. Library Trends, 59(4), 686–706. DOI: 10.1353/lib.2011.0022
Tirilly, P., Huang, C., Jeong, W., Mu, X., Xie, I., and Zhang, J. (2012). Image similarity as assessed by users: A quantitative study, presented at ASIST 2012, October 26–31, 2012, Baltimore, MD. DOI: 10.1002/meet.14504901180
Yoon, J. W. (2009). Toward a user-oriented thesaurus for non-domain-specific image collections. Information Processing and Management 45, 452–468. DOI: 10.1016/j.ipm.2009.03.004
Yoon, J. W. (2010). Utilizing quantitative users’ reactions to represent affective meanings of an image. Journal of the American Society for Information Science and Technology, 61(7), 1345–1359. DOI: 10.1002/asi.21342.
Yoon, J. W. (2011a). A comparative study of methods to explore searchers’ affective perceptions of images. IR Information Research, 16(2).
Yoon, J. W. (2011b). Searching images in daily life. Library & Information Science Research, 33, 269–275. DOI: 10.1016/j.lisr.2011.02.003
Yoon, J. W. and Chung, E. (2011). Understanding image needs in daily life by analyzing questions in a social Q&A site. Journal of the American Society for Information Science and Technology, 62(11), 2201–2213. DOI: 10.1002/asi.21637
van Eck, N. J., & Waltman, L. (2014). Visualizing Bibliometric Networks. In Y. Ding, R. Rousseau, & D. Wolfram (Eds.), Measuring Scholarly Impact (pp. 285–320). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-10377-8_13
Walsh, I., Holton, J. A., Bailyn, L., Fernandez, W., Levina, N., and Glaser, B. (2015). What grounded theory is . . . A critically reflective conversation among scholars. Organizational Research Methods, 18(4), 581–599. DOI: 10.1177/1094428114565028
Westman, S. and Oittinen, P. (2006). Image Retrieval by End-users and Intermediaries in a Journalistic Work Context. Information Interaction in Context: International Symposium on Information Interaction in Context: IiiX: Copenhagen, Denmark, October 18–20, 2006, 102–110. DOI: 10.1145/1164820.1164843
White, H. D., & McCain, K. W. (1998). Visualizing a discipline: An author co-citation analysis of information science, 1972-1995. Journal of the American Society for Information Science, 49(4), 327–355.
Zeng, M. L., Gracy, K. F., and Žumer, M. (2014). Using a semantic analysis tool to generate subject access points: A study using Panofsky’s Theory and two research samples, presented at the International ISKO Conference, May 19–22, 2014, Krakow, Poland.
Ørnager, S. & Lund, H. (2018) Images in social media. Categorization and organization of images and their collections. S.l.: Morgan & Claypool
Publiceret
2019-08-26
Citation/Eksport
Ørnager, S., & Lund, H. (2019). Billedindeksering og sociale medier. Nordisk Tidsskrift for Informationsvidenskab Og Kulturformidling, 8(1), 2-21. https://doi.org/10.7146/ntik.v8i1.115599
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