References
- Aggarwal, C. C., & Zhai, C. X. (2013). Mining text data. Mining text data (Vol. 9781461432). https://doi.org/10.1007/978-1-4614-3223-4
- Agrawal, A., Boese, M. J., & Sarker, S. (2010). A review of the HCI literature in IS: The missing links of computer-mediated communication, culture, and interaction. Lima, Peru: AMCIS (p. 523).
- Akgun, M., Cagiltay, K., & Zeyrek, D. (2010). The effect of apologetic error messages and mood states on computer users’ self-appraisal of performance. Journal of Pragmatics, 42(9), 2430–2448. https://doi.org/10.1016/j.pragma.2009.12.011
- Akoumianakis, D., & Stephanidis, C. (1989). Universal design in HCI: A critical review of current research and practice. Science And Technology, 14, 4pp.
- Amado, A., Cortez, P., Rita, P., & Moro, S. (2018). Research trends on big data in marketing: A text mining and topic modeling based literature analysis. European Research on Management and Business Economics, 24(1), 1–7. https://doi.org/10.1016/j.iedeen.2017.06.002
- Anshuman, S., & Kumar, B. (2004). Architecture and HCI: A review of trends towards an integrative approach to designing responsive space. International Journal of IT in Architecture, Engineering and Construction, 2(4), 273–284.
- Aryana, B., & Øritsland, T. A. (2010). Culture and mobile HCI: A review. Proceedings of NordDesign 2010, the 8th International NordDesign Conference, Göteborg, Sweden.
- Atkinson, J., & Campos, D. (2016). Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers. Expert Systems with Applications, 47, 35–41. https://doi.org/10.1016/j.eswa.2015.10.049
- Berg, G. A. (2000). Human-computer interaction (HCI) in educational environments: implications of understanding computers as media. Journal of Educational Multimedia and Hypermedia, 9(4), 347–368. http://www.editlib.org/p/9550
- Blei, D. M. (2012). Probabilistic topic models. Communications of the ACM, 55(4), 77–84. https://doi.org/10.1145/2133806.2133826
- Blei, D. M., Edu, B. B., Ng, A. Y., Edu, A. S., Jordan, M. I., & Edu, J. B. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(4–5), 993–1022. https://doi.org/10.1162/jmlr.2003.3.4-5.993
- Blei, D. M., & Lafferty, J. D. (2007). Correction: A correlated topic model of Science. The Annals of Applied Statistics, 1(2), 634–634. https://doi.org/10.1214/07-aoas136
- Botta, A., De Donato, W., Persico, V., & Pescapé, A. (2016). Integration of Cloud computing and Internet of Things: A survey. Future Generation Computer Systems, 56, 684–700. https://doi.org/10.1016/j.future.2015.09.021
- Bush, V. (1945). As we may think the atlantic. The Atlantic.
- Cagiltay, K. (1999). Culture and its effects on human-computer-interaction. Proceedings of world conference on educational multimedia, hypermedia and telecommunications (p. 1626), Washington, DC.
- Çağıltay, K. (2018). İnsan bilgisayar etkileşimi ve kullanılabilirlik mühendisliği: Teoriden pratiğe. Seçkin Yayınevi.
- Caroux, L., Isbister, K., Le Bigot, L., & Vibert, N. (2015). Player-video game interaction: A systematic review of current concepts. Computers in Human Behavior, 48, 366–381. https://doi.org/10.1016/j.chb.2015.01.066
- Carter, M., Downs, J., Nansen, B., Harrop, M., & Gibbs, M. (2014). Paradigms of games research in HCI: A review of 10 years of research at CHI. CHI PLAY 2014 - Proceedings of the 2014 Annual Symposium on Computer-Human Interaction in Play, Toronto, ON. https://doi.org/10.1145/2658537.2658708
- Chakraborty, B. K., Sarma, D., Bhuyan, M. K., & MacDorman, K. F. (2017). Review of constraints on vision-based gesture recognition for human–computer interaction. IET Computer Vision, 12(1), 3–15. https://doi.org/10.1049/iet-cvi.2017.0052
- Chapanis, A. (1965). Man-machine engineering.
- Choi, H. S., Lee, W. S., & Sohn, S. Y. (2017). Analyzing research trends in personal information privacy using topic modeling. Computers and Security, 67, 244–253. https://doi.org/10.1016/j.cose.2017.03.007
- Cisco, T. (2013). Cisco visual networking index: Global mobile data traffic forecast update, 2012–2017. Cisco Public Information, 26, 27.
- Clemmensen, T., & Roese, K. (2009). An overview of a decade of journal publications about culture and human-computer interaction (HCI). IFIP Working Conference on Human Work Interaction Design (pp. 98–112), Pune, India.
- Coursaris, C. K., & Bontis, N. (2012). A meta review of HCI literature: Citation impact and research productivity rankings. Sighci 2012, 9, 1–5. http://aisel.aisnet.org/sighci2012/9
- Coursaris, C. K., & Kim, D. (2011). A meta-analytical review of empirical mobile usability studies. Journal of Usability Studies, 6(3), 117–171.
- Coursaris, C. K., & Kim, D. J. (2006). A qualitative review of empirical mobile usability studies. Association for Information Systems - 12th Americas Conference On Information Systems, AMCIS 2006 (Vol.5, pp. 2873–2879), Acapulco, Mexico.
- Cunliffe, D. (2000). Developing usable Web sites - A review and model. Internet Research.
- Dearden, A., & Finlay, J. (2006). Pattern languages in HCI: A critical review. Human-Computer Interaction, 21(1), 49–102. https://doi.org/10.1207/s15327051hci2101_3
- Debortoli, S., Müller, O., Junglas, I., & Vom Brocke, J. (2016). Text mining for information systems researchers: An annotated topic modeling tutorial. Communications of the Association for Information Systems.
- Dillon, A., & Watson, C. (1996). User analysis in HCI - The historical lessons from individual differences research. International Journal of Human Computer Studies, 45(6), 619–637. https://doi.org/10.1006/ijhc.1996.0071
- Dix, A. (2009). Human-computer interaction. Springer.
- Dix, A. (2017). Human–computer interaction, foundations and new paradigms. Journal of Visual Languages and Computing, 42, 122–134. https://doi.org/10.1016/j.jvlc.2016.04.001
- Duarte, E. F., & Baranauskas, M. C. C. (2016). Revisiting the three HCI waves: A preliminary discussion on philosophy of science and research paradigms. ACM International Conference Proceeding Series, Salvador, Brazil. https://doi.org/10.1145/3033701.3033740
- Geman, S., & Geman, D. (1984). Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI, 6(6), 721–741. https://doi.org/10.1109/TPAMI.1984.4767596
- Goodrich, M. A., & Schultz, A. C. (2007). Human-robot interaction: A survey. Foundations and Trends in Human-Computer Interaction, 1(3), 203–275. https://doi.org/10.1561/1100000005
- Gordon, W. A. (2005). The interface between cognitive impairments and access to information technology. ACM SIGACCESS Accessibility and Computing, (83), 3–6. https://doi.org/10.1145/1102187.1102188
- Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(Suppl. 1), 5228–5235. https://doi.org/10.1073/pnas.0307752101
- Griffiths, T. L., Steyvers, M., & Tenenbaum, J. B. (2007). Topics in semantic representation. Psychological Review, 114(2), 211. https://doi.org/10.1037/0033-295X.114.2.211
- Grudin, J. (2012). Introduction: A moving target - the evolution of human-computer interaction. Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies and Emerging Applications. https://doi.org/10.1201/b11963-1
- Grün, B., & Hornik, K. (2011). topicmodels : An R package for fitting topic models. Journal of Statistical Software, 40(13), 1–30. https://doi.org/10.18637/jss.v040.i13
- Gurcan, F. (2018a). Major research topics in big data: A literature analysis from 2013 to 2017 using probabilistic topic models. 2018 International Conference on Artificial Intelligence and Data Processing (IDAP) (pp. 1–4), Malatya, Turkey.
- Gurcan, F. (2018b). Multi-class classification of Turkish texts with machine learning algorithms. 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1–5), Ankara, Turkey.
- Gurcan, F. (2019). Extraction of core competencies for big data: implications for competency-based engineering education. International Journal of Engineering Education, 35(4), 1110–1115.
- Gurcan, F., & Cagiltay, N. E. (2019). Big data software engineering: analysis of knowledge domains and skill sets using LDA-based topic modeling. IEEE Access, 7, 82541–82552. https://doi.org/10.1109/ACCESS.2019.2924075
- Gurcan, F., & Kose, C. (2017). Analysis of software engineering industry needs and trends: implications for education. International Journal of Engineering Education, 33(4), 1361–1368.
- Gurcan, F., & Sevik, S. (2019). Human-computer interaction: a literature analysis from 1998 to 2018 using automated text mining. 1st International Informatics and Software Engineering Conference: Innovative Technologies for Digital Transformation, IISEC 2019 - Proceedings, Ankara, Turkey. https://doi.org/10.1109/UBMYK48245.2019.8965599
- Hall, D., Jurafsky, D., & Manning, C. D. (2008). Studying the history of ideas using topic models. EMNLP 2008-2008 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference: A Meeting of SIGDAT, a Special Interest Group of the ACL, Hawaii, USA.
- Hao, T., Chen, X., Li, G., & Yan, J. (2018). A bibliometric analysis of text mining in medical research. Soft Computing, 22(23), 7875–7892. https://doi.org/10.1007/s00500-018-3511-4
- Harrison, R., Flood, D., & Duce, D. (2013). Usability of mobile applications: Literature review and rationale for a new usability model. Journal of Interaction Science, 1(1). https://doi.org/10.1186/2194-0827-1-1
- Harrison, S., Tatar, D., & Sengers, P. (2007). The three paradigms of HCI. Alt. Chi. Session at the SIGCHI …. https://doi.org/10.1234/12345678
- Hewett, T. T., Baecker, R., Card, S., Carey, T., Gasen, J., Mantei, M., … Verplank, W. (1992). ACM SIGCHI curricula for human-computer interaction. ACM.
- Hinze-Hoare, V. (2007). The review and analysis of human computer interaction (HCI) principles. ArXiv Preprint ArXiv:0707.3638.
- Hochheiser, H., & Lazar, J. (2007). HCI and societal issues: A framework for engagement. International Journal of Human-Computer Interaction, 23(3), 339–374. https://doi.org/10.1080/10447310701702717
- Hornbæk, K., & Hertzum, M. (2017). Technology acceptance and user experience: A review of the experiential component in HCI. ACM Transactions on Computer-Human Interaction, 24(5), 1–30. https://doi.org/10.1145/3127358
- Hornbæk, K., Mottelson, A., Knibbe, J., & Vogel, D. (2019). What do we mean by “interaction”? An analysis of 35 years of ChI. ACM Transactions on Computer-Human Interaction, 26(4), 4. https://doi.org/10.1145/3325285
- Hurtienne, J. (2009). Cognition in HCI: An ongoing story. Human Technology: An Interdisciplinary Journal on Humans in ICT Environments, 5(1), 12–28. https://doi.org/10.17011/ht/urn.20094141408
- Inkpen, K. (1997). Three important research agendas for educational multimedia: Learning, children, and gender. Proceedings of Conference on Educational Multimedia,\nHypermedia & Telecommunications (EdMedia’97), Calgary, USA. https://doi.org/10.1.1.54.4439
- Kantardzic, M. (2011). Data mining: concepts, models, methods, and algorithms: second edition. Data Mining: Concepts, Models, Methods, and Algorithms: Second Edition.
- Karacan, H., & Cagiltay, K. (2009). The role of attention for visual perception in desktop virtual reality environments. 15th Americas Conference on Information Systems 2009, AMCIS 2009, San Francisco, CA.
- Karl, A., Wisnowski, J., & Rushing, W. H. (2015). A practical guide to text mining with topic extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326–340. https://doi.org/10.1002/wics.1361
- Karray, F., Alemzadeh, M., Abou Saleh, J., & Nours Arab, M. (2008). Human-computer interaction: overview on state of the art. International Journal on Smart Sensing and Intelligent Systems, 1(1), 137–159. https://doi.org/10.21307/ijssis-2017-283
- Kaya, H., Salah, A. A., Karpov, A., Frolova, O., Grigorev, A., & Lyakso, E. (2017). Emotion, age, and gender classification in children’s speech by humans and machines. Computer Speech and Language, 46, 268–283. https://doi.org/10.1016/j.csl.2017.06.002
- Kim, G. J., & Group, F. (2015). Human – Computer Interaction Fundamentals and Practice. Human Computer Interaction: Fundamentals and Practice, 1–12. CRC Press. http://www.ittoday.info/Excerpts/HCI.pdf
- Kjeldskov, J., & Graham, C. (2003). A review of mobile HCI research methods. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
- Kjeldskov, J., & Paay, J. (2012). A longitudinal review of mobile HCI research methods. Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services (pp. 69–78), San Francisco, CA.
- Kyriakoullis, L., & Zaphiris, P. (2016). Culture and HCI: A review of recent cultural studies in HCI and social networks. Universal Access in the Information Society, 15(4), 629–642. https://doi.org/10.1007/s10209-015-0445-9
- Li, Zhang, P., & Li, L. (2005). The intellectual development of human-computer interaction research: A critical assessment of the MIS literature (1990-2002). Journal of the Association for Information Systems, 6(11), 227–292. https://doi.org/10.17705/1jais.00070
- Li, C., Wang, H., Zhang, Z., Sun, A., & Ma, Z. (2016). Topic modeling for short texts with auxiliary word embeddings. SIGIR 2016 - Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, Pisa, Italy. https://doi.org/10.1145/2911451.2911499
- Luppicini, R. (2013). Moral, ethical, and social dilemmas in the age of technology: Theories and practice. Moral, Ethical, and Social Dilemmas in the Age of Technology: Theories and Practice. https://doi.org/10.4018/978-1-4666-2931-8
- Magnenat-Thalmann, N., Yuan, J., Thalmann, D., & You, B.-J. (2016). Context aware human-robot and human-agent interaction. Springer.
- Minguillon, J., Lopez-Gordo, M. A., & Pelayo, F. (2017). Trends in EEG-BCI for daily-life: Requirements for artifact removal. Biomedical Signal Processing and Control, 31, 407–418. https://doi.org/10.1016/j.bspc.2016.09.005
- Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of web of science and scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5
- Moro, S., Cortez, P., & Rita, P. (2015). Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation. Expert Systems with Applications, 42(3), 1314–1324. https://doi.org/10.1016/j.eswa.2014.09.024
- Murphy, R. R., Nomura, T., Billard, A., & Burke, J. L. (2010). Human–robot interaction. IEEE Robotics & Automation Magazine, 17(2), 85–89. https://doi.org/10.1109/MRA.2010.936953
- Nguyen, H. T., & Caplier, A. (2015). Local patterns of gradients for face recognition. IEEE Transactions on Information Forensics and Security, 10(8), 1739–1751.
- Nichols, L. G. (2014). A topic model approach to measuring interdisciplinarity at the National Science Foundation. Scientometrics, 100(3), 741–754. https://doi.org/10.1007/s11192-014-1319-2
- Norman, D. A., & Draper, S. W. (1986). Cognitive Engineering, in User centered system design: New Perspectives on Human-Computer Interaction. User centered system design: New perspectives on human-computer interaction.
- Ocak, N., & Cagiltay, K. (2017). Comparison of cognitive modeling and user performance analysis for touch screen mobile interface design. International Journal of Human-Computer Interaction, 33(8), 633–641. https://doi.org/10.1080/10447318.2016.1274160
- Perez-Gaspar, L. A., Caballero-Morales, S. O., & Trujillo-Romero, F. (2016). Multimodal emotion recognition with evolutionary computation for human-robot interaction. Expert Systems with Applications, 66, 42–61. https://doi.org/10.1016/j.eswa.2016.08.047
- Peter, C., Beale, R., Crane, E., & Axelrod, L. (2007). Emotion in HCI. People and Computers XXI HCI. But Not as We Know It - Proceedings of HCI 2007: The 21st British HCI Group Annual Conference, San Francisco, CA.
- Picard, R. W. (2003). Affective computing: Challenges. International Journal of Human Computer Studies, 59(1–2), 55–64. https://doi.org/10.1016/S1071-5819(03)00052-1
- Porter, M. (2001). Snowball: A language for stemming algorithms. Snowball.
- Qin, X., Tan, C. W., & Clemmensen, T. (2017). Context-awareness and mobile HCI: Implications, challenges and opportunities. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vancouver, Canada. https://doi.org/10.1007/978-3-319-58481–2_10
- Sahoo, B., & Kumar, A. (2018). Indexing and abstracting bibliographic electronic database: A comparative analysis. International Journal of Information Dissemination and Technology, 8(2), 99. https://doi.org/10.5958/2249-5576.2018.00021.3
- Satyanarayanan, M. (2015). A brief history of cloud offload: A personal journey from odyssey through cyber foraging to cloudlets. ACM SIGMOBILE Mobile Computing and Communications Review, 18(4), 19–23. https://doi.org/10.1145/2721914.2721921
- Shackel, B. (1959). Ergonomics for a computer. Design, 120, 36–39.
- Shneiderman, B., & Plaisant, C. (2010). Designing the user interface: Strategies for effective human-computer interaction. Pearson Education India.
- Song, M., & Kim, S. Y. (2013). Detecting the knowledge structure of bioinformatics by mining full-text collections. Scientometrics, 96(1), 183–201. https://doi.org/10.1007/s11192-012-0900-9
- Srivastava, A. N., & Sahami, M. (2009). Text mining: Classification, clustering, and applications. CRC Press.
- Stanney, K. M., Mourant, R. R., & Kennedy, R. S. (1998). Human factors issues in virtual environments: A review of the literature. Presence: Teleoperators and Virtual Environments, 7(4), 327–351. https://doi.org/10.1162/105474698565767
- Tan, D., & Nijholt, A. (2010). Brain-computer interfaces and human-computer interaction. In Brain-computer interfaces (pp. 3–19). London: Springer. https://doi.org/10.1007/978-1-84996-272-8_1
- Te’eni, D., Carey, J., & Zhang, P. (2007). Human-computer interaction: Developing effective organizational information systems. John Wiley & Sons, Inc.
- Thrun, S. (2004). Toward a framework for human-robot interaction. Human-Computer Interaction, 19(1–2), 9–24. https://doi.org/10.1207/s15327051hci1901&2_2
- Turk, M. (2014). Multimodal interaction: A review. Pattern Recognition Letters, 36, 189–195. https://doi.org/10.1016/j.patrec.2013.07.003
- Wallach, H. M. (2006). Topic modeling: beyond bag-of-words. In Proceedings of the 23rd international conference on Machine learning (pp. 977–984). Pittsburgh, PA: Carnegie Mellon University. https://doi.org/10.1145/1143844.1143967
- Weyrich, M., & Ebert, C. (2016). Reference architectures for the internet of things. IEEE Software, 33(1), 112–116. https://doi.org/10.1109/MS.2016.20
- Wobbrock, J. O., & Kientz, J. A. (2016). Research contributions in human-computer interaction. Interactions, 23(3), 38–44. https://doi.org/10.1145/2907069
- Wolpaw, J. R., & Wolpaw, E. W. (2012). Brain-Computer Interfaces: Principles and Practice. Brain-Computer Interfaces: Principles and Practice. https://doi.org/10.1093/acprof:oso/9780195388855.001.0001
- Yang, F., & Shen, F. (2018). Effects of web interactivity: A meta-analysis. Communication Research, 45(5), 635–658. https://doi.org/10.1177/0093650217700748
- Zhang, L., Scialdone, N., & Carey, J. (2009). The intellectual advancement of human-computer interaction research: A critical assessment of the MIS literature (1990-2008). AIS Transactions on Human-Computer Interaction, 1(3), 55–107. https://doi.org/10.17705/1thci.00007
- Zuo, Y., Wu, J., Zhang, H., Lin, H., Wang, F., Xu, K., & Xiong, H. (2016). Topic modeling of short texts: A pseudo-document view. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA. https://doi.org/10.1145/2939672.2939880