Skip to main content
SpringerLink
Log in

A principle of designing infographic for visualization representation of tourism social big data

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

With the development of technology, people have more needs for the visual representation of interface information. Visualization, image and interaction have all become the design directions of user interfaces in recent years. The purpose of this study is to collect the user’s perception of the chart through experiments, explore the visualization of the chart presentation, and establish the “The principle of infographic design”. This study used the Octopus web data collection software to collect travel-related social big data of Facebook fan page and produce six different types of charts (a total of ten charts) by Tableau visual software that used as the experimental chart material. Relevant visual factors were derived through experiments. The experimental results found the chart element size, color, color gradients, data, sorting, and chart title will affect the results of the user to watch the chart. This study suggests the following induction 4 points to establish the presentation of information charts to provide chart designer: (1) to appropriate use of color to show the infographic, (2) marked the data to help users quickly understand the information, (3) sort the size of the element, so that users can have a sequential view, and (4) make the best use of different sizes, to convey the difference in the proportion of users.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Barhamgi M, Masmoudi A, Lara-Cabrera R, Camacho D (2018) Social networks data analysis with semantics: application to the radicalization problem. J Ambient Intell Hum Comput 2018:1–15

    Google Scholar 

  • Bello-Orgaz G, Jung JJ, Camacho D (2016) Social big data: recent achievements and new challenges. Inf Fusion 28:45–59

    Article  PubMed  Google Scholar 

  • Card SK, Mackinlay JD, Shneiderman B (1999) Readings in information visualization: using vision to think. Morgan Kaufmann, Burlington

    Google Scholar 

  • Cheng M-H, Wu Y-C, Chen M-C (2016) Television meets facebook: the correlation between TV ratings and social media. Am J Ind Bus Manag 6(03):282

    Google Scholar 

  • Dur BIU (2014) Data visualization and infographics in visual communication design education at the age of information. J Arts Hum 3(5):39

    Google Scholar 

  • eBiZ MBA (2015/10) Top 15 most popular social networking sites. http://www.ebizmba.com/articles/social-networking-websites. Accessed Jan 2017

  • Ericsson KA, Simon HA (1980) Verbal reports as data. Psychol Rev 87:215–252

    Article  Google Scholar 

  • Fonteyn ME, Kuipers B, Grobe SJ (1993) A description of think aloud method and protocol analysis. Qual Health Res 3(4):430–441

    Article  Google Scholar 

  • Gartner (2016) Gartner survey reveals investment in big data is up but fewer organizations plan to invest. http://www.gartner.com/newsroom/id/3466117. Accessed Jan 2017

  • Gordon GR, Choi HB, Rungta RL, Ellis-Davies GC, MacVicar BA (2008) Brain metabolism dictates the polarity of astrocyte control over arterioles. Nature 456(7223):745–749

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  • Guo T, Guo B, Ouyang Y, Yu Z, Lam JCK, Li VOK (2018) CrowdTravel: scenic spot profiling by using heterogeneous crowdsourced data. J Ambient Intell Hum Comput 9(6):2051–2060

    Article  Google Scholar 

  • Harvey A (2013) User experience: what is it and why should i care? http://usabilitygeek.com/user-experience/. Accessed Jan 2017

  • International Telecommunication Union (ITU) (2005) The Internet of Things—executive summary. ITU Internet Reports

  • Ishikawa H (2015) Social big data mining. CRC, Boca Raton

    Book  Google Scholar 

  • ISO (2010) ISO 9241-210:2010(en). Ergonomics of human-system interaction—part 210: human-centred design for interactive systems

  • Laney D (2001) 3D data management: controlling data volume, velocity and variety. META Group Res Note 6:70

    Google Scholar 

  • Law E, Roto V, Vermeeren AP, Kort J, Hassenzahl M (2008) Towards a shared definition of user experience. In: CHI’08 extended abstracts on Human factors in computing systems. ACM, pp 2395–2398

  • Li Z, Carberry S, Fang H, McCoy KF, Peterson K, Stagitis M (2015) A novel methodology for retrieving infographics utilizing structure and message content. Data Knowl Eng 100:191–210

    Article  Google Scholar 

  • Lin YC, Yeh CH, Wei CC (2013) How will the use of graphics affect visual aesthetics? A user-centered approach for web page design. Int J Hum Comput Stud 71(3):217–227

    Article  Google Scholar 

  • Lund AM (2001) Measuring usability with the USE questionnaire. Usabil Interface 8(2):3–6

    Google Scholar 

  • Mahlke S (2005) Studying affect and emotions as important parts of the user experience. In: Workshop on the role of emotion in human-computer interaction, HCI conference, pp 2001–2002

  • McAfee A, Brynjolfsson E (2012) Big Data: the management revolution. Harvard Business Review, Harvard

    Google Scholar 

  • Michel CM, Henggeler B, Brandeis D, Lehmann D (1993) Localization of sources of brain alpha/theta/delta activity and the influence of the mode of spontaneous mentation. Physiol Meas 14(4A):A21

    Article  PubMed  Google Scholar 

  • Pangestu H, Karsen M (2016) Evaluation of usability in online learning. In: 2016 International conference on information management and technology (ICIMTech). Bandung, Indonesia

  • Scheaffer RL, Watkins AE, Landwehr JM (1998) What every high-school graduate should know about statistics. In: Reflections on statistics: learning, teaching, and assessment in grades K-12, pp 3–31

  • Sedlmair M, Meyer M, Munzner T (2012) Design study methodology: reflections from the trenches and the stacks. IEEE Trans Vis Comput Gr 18(12):2431–2440

    Article  CAS  Google Scholar 

  • Shih BH (2016) Research and application on the infographic design: a case study of propaganda of recruit students of applied arts at Fu Jen Catholic University. Master’s thesis, Fu Jen Catholic University, Taiwan

  • Smart Insights (2017) What happens online in 60 s? http://www.smartinsights.com/internet-marketing-statistics/happens-online-60-seconds/. Accessed Jan 2017

  • Smiciklas M (2012) The power of infographics: using pictures to communicate and connect with your audiences. Que, London

    Google Scholar 

  • Soubra D (2012) The 3Vs that define big data. In: Data science central. Retrieved from https://www.datasciencecentral.com/forum/topics/the-3vs-that-define-big-data

  • Tsai MJ (2015) A study of evaluation for information graphics based on user experience. Master’s thesis, Shih Hsin University, Taiwan

  • Tube Graphics (2012) The logic of design: INFOGRAPHICS deeply rooted in the visual law. Flag, Taipei

    Google Scholar 

  • Vicente JL (2007) Visualizar: introduction. http://medialab-prado.es/article/visualizar. Accessed Jan 2017

  • White C (2012) MapReduce and the data scientist. BI Res 2012:1–18

    Google Scholar 

  • Yang SM (2016) Implementation of a brainwave data analysis platform. Master’s thesis of Department of Multimedia Design, National Taichung University of Science and Technology

  • Zeng YT (2014) Measuring attitudes toward the TV commercials through EEG analysis, expression observation, and questionnaire. Master’s thesis of Department of Business Administration, Taipei University

Download references

Acknowledgements

The authors sincerely thanks to the financial support from Ministry of Science and Technology of Taiwan (MOST 105-2221-E-327-026).

Author information

Authors and Affiliations

  1. Department of Information Management, National Kaohsiung University of Science and Technology, No. 2 Jhuoyue Rd, Nanzih, Kaohsiung, Taiwan, ROC

    Kuo-Wei Su & Yu-Wun Wang

  2. Department of Industrial Management, Vanung University, No. 1 Vannung Rd, Chungli, Taoyuan, Taiwan, ROC

    Cheng-Li Liu

Authors
  1. Kuo-Wei Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cheng-Li Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yu-Wun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kuo-Wei Su.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Su, KW., Liu, CL. & Wang, YW. A principle of designing infographic for visualization representation of tourism social big data. J Ambient Intell Human Comput 14, 14509–14529 (2023). https://doi.org/10.1007/s12652-018-1104-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-018-1104-9

Keywords

Search

Navigation