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Analysing public sentiment towards robotic surgery: an X (formerly Twitter) based study

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Abstract

The surgical field is always evolving, as new techniques and tools are developed. Robotic technology has been playing an important role in surgical procedures, especially in complex surgeries. Robotic surgery is intricately connected with minimally invasive procedures, where surgeries are performed through small incisions. It may also find occasional use in different categories of open surgeries. There are many benefits to robotic surgery, including that it is minimally invasive and can be done without incision. The downside to robotic surgery is that it can be expensive, and the quality of the results may not be good. Advancements in robotics are introducing fresh benefits to the operating room. Nevertheless, there are concerns voiced by individuals about the safety and effectiveness of robotic surgery. In order to gain a better understanding of these issues, an exploration was carried out involving sentiment analysis of online discussions concerning robotic surgery. This analysis focused on tweets shared on X (formerly Twitter). Furthermore, this research paper utilizes “RoboSens” algorithm which is a domain-specific customization based on the VADER sentiment analysis model, specifically tailored to analyze public opinion on robotic surgery using X data. The majority of X users worldwide (44.3%) were found to have a neutral opinion of robotic surgery. These people did not completely discourage robotic surgery but are still reluctant to accept it in all types of surgical treatments. Around 39.3% of people worldwide feel enthusiastic about robotic surgery while 16.4% completely discourage it.

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Data Availability

The dataset generated during and/or analyzed during the current study is of Service but are available from the the corresponding author on reasonable request.

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Funding

For this research, no funding was provided.

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Author notes

  1. Smriti Kumari, Anamika Sharma, Ankit Gupta, Sarabjeet Singh and Ravi Verma have contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology (Degree Wing), Sector 26, Chandigarh, 160019, India

    Smriti Kumari, Anamika Sharma, Amit Chhabra, Ankit Gupta, Sarabjeet Singh & Ravi Verma

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  1. Smriti Kumari
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  2. Anamika Sharma
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  3. Amit Chhabra
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  4. Ankit Gupta
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  5. Sarabjeet Singh
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  6. Ravi Verma
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Contributions

S.K. Wrote and edited the manuscript and conducted the literature review. A.S. Implemented the machine learning model for sentiment analysis. A.C. Guided sentiment analysis, edited manuscript. A.G. Directed research, and edited manuscript. R.V. Assisted with data collection and machine learning model implementation. S.S. Prepared manuscript and edited manuscript. All authors reviewed the manuscript.

Corresponding author

Correspondence to Amit Chhabra.

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Kumari, S., Sharma, A., Chhabra, A. et al. Analysing public sentiment towards robotic surgery: an X (formerly Twitter) based study. Soc. Netw. Anal. Min. 14, 61 (2024). https://doi.org/10.1007/s13278-024-01226-9

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