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Advanced Computing and Systems for Security pp 73–88Cite as

Readability Analysis of Textual Content Using Eye Tracking

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 897))

Abstract

Characterization of silent reading involves a joint analysis of the reading material and reader’s capacity to assimilate the content. The amount of mental workload, to understand a content, reflects the overall cognitive load which is commonly measured using electrophysiological signals. Eye movement provides a direct means of evaluating one’s reading characteristics in much finer details. In this paper, we use a commercially available low-cost eye-tracking device, EyeTribe. We analyze the eye movement behavior to compare readability of textual contents and also characterize an individual’s reading profile. The experiment is performed using two types of textual contents significantly separated in difficulty level as evaluated using standard readability indices. The Flesch-Kincaid Grade Level for one type varies between 3 and 6 and the other between 13 and 16. Eye gaze analysis is done on features related to fixation and saccade using both global and local features. Results indicate the difference in content is reflected in global features and individual level variations, for a given type of content, are observed in the entropy derived from local features.

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Acknowledgements

The authors would like to thank the participants for their cooperation during the experiment and providing the data for the analysis. The data is anonymized for the processing and informed consent was taken from the participants. The data collection protocol followed Helsinki Human Research guidelines (https://www.helsinki.fi/en/research/research-environment/research-ethics).

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Authors and Affiliations

  1. TCS Research & Innovation, Tata Consultancy Services, Kolkata, India

    Aniruddha Sinha

  2. Department of Computer Science & Engineering, Jadavpur University, Kolkata, India

    Rikayan Chaki, Bikram De Kumar & Sanjoy Kumar Saha

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  1. Aniruddha Sinha
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  2. Rikayan Chaki
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  3. Bikram De Kumar
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  4. Sanjoy Kumar Saha
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Corresponding author

Correspondence to Aniruddha Sinha .

Editor information

Editors and Affiliations

  1. A.K. Choudhury School of Information Technology, University of Calcutta, Kolkata, West Bengal, India

    Rituparna Chaki

  2. Dipartimento di Scienze Ambientali, Informatica e Statistica, Università Ca’ Foscari Venezia, Mestre, Venice, Italy

    Agostino Cortesi

  3. Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

    Khalid Saeed

  4. Department of Computer Science and Engineering, University of Calcutta, Kolkata, West Bengal, India

    Nabendu Chaki

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Sinha, A., Chaki, R., De Kumar, B., Saha, S.K. (2019). Readability Analysis of Textual Content Using Eye Tracking. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 897. Springer, Singapore. https://doi.org/10.1007/978-981-13-3250-0_6

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