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Erschienen in: Social Network Analysis and Mining 1/2024

01.12.2024 | Original Article

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

verfasst von: Smriti Kumari, Anamika Sharma, Amit Chhabra, Ankit Gupta, Sarabjeet Singh, Ravi Verma

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2024

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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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Literatur
Zurück zum Zitat Akande ON, Nnaemeka ES, Abikoye OC, Akande, HB, Balogun A, Ayoola J (2022) TWEERIFY: a web-based sentiment analysis system using rule and deep learning techniques. Proceedings of international conference on computational intelligence and data engineering: Iccide 2021, pp 75–87 Akande ON, Nnaemeka ES, Abikoye OC, Akande, HB, Balogun A, Ayoola J (2022) TWEERIFY: a web-based sentiment analysis system using rule and deep learning techniques. Proceedings of international conference on computational intelligence and data engineering: Iccide 2021, pp 75–87
Zurück zum Zitat Aldousari SA, Buabbas AJ, Yaiesh SM, Alyousef RJ, Alenezi AN (2021) Multiple perceptions of robotic-assisted surgery among surgeons and patients: a cross-sectional study. J Robot Surg 15:529–538CrossRefPubMed Aldousari SA, Buabbas AJ, Yaiesh SM, Alyousef RJ, Alenezi AN (2021) Multiple perceptions of robotic-assisted surgery among surgeons and patients: a cross-sectional study. J Robot Surg 15:529–538CrossRefPubMed
Zurück zum Zitat Alemzadeh H, Raman J, Leveson N, Kalbarczyk Z, Iyer RK (2016) Adverse events in robotic surgery: a retrospective study of 14 years of FDA data. PLoS ONE 11(4):e0151470CrossRefPubMedPubMedCentral Alemzadeh H, Raman J, Leveson N, Kalbarczyk Z, Iyer RK (2016) Adverse events in robotic surgery: a retrospective study of 14 years of FDA data. PLoS ONE 11(4):e0151470CrossRefPubMedPubMedCentral
Zurück zum Zitat Ashrafian H, Clancy O, Grover V, Darzi A (2017) The evolution of robotic surgery: surgical and anaesthetic aspects. BJA British J Anaesth 119(suppl–1):i72–i84CrossRef Ashrafian H, Clancy O, Grover V, Darzi A (2017) The evolution of robotic surgery: surgical and anaesthetic aspects. BJA British J Anaesth 119(suppl–1):i72–i84CrossRef
Zurück zum Zitat Ashrafian H, Darzi A, Athanasiou T (2015) A novel modification of the turing test for artificial intelligence and robotics in healthcare. Int J Med Robot Comput Assis Surg 11(1):38–43CrossRef Ashrafian H, Darzi A, Athanasiou T (2015) A novel modification of the turing test for artificial intelligence and robotics in healthcare. Int J Med Robot Comput Assis Surg 11(1):38–43CrossRef
Zurück zum Zitat Cambria E, Grassi M, Hussain A, Havasi C (2012) Sentic computing for social media marketing. Multimed Tools Appl 59:557–577CrossRef Cambria E, Grassi M, Hussain A, Havasi C (2012) Sentic computing for social media marketing. Multimed Tools Appl 59:557–577CrossRef
Zurück zum Zitat Chhabra A, Sharma A, Chhabra K, Chhabra A (2023) A statistical analysis of sentiment over different social platforms on drug usage across high, middle and low-income countries. Scalable Comput Pract Exper 24(4):971–984CrossRef Chhabra A, Sharma A, Chhabra K, Chhabra A (2023) A statistical analysis of sentiment over different social platforms on drug usage across high, middle and low-income countries. Scalable Comput Pract Exper 24(4):971–984CrossRef
Zurück zum Zitat Elbagir S, Yang J (2019) Twitter sentiment analysis using natural language toolkit and Vader sentiment. In: Proceedings of the international multiconference of engineers and computer scientists, Vol. 122, pp 16 Elbagir S, Yang J (2019) Twitter sentiment analysis using natural language toolkit and Vader sentiment. In: Proceedings of the international multiconference of engineers and computer scientists, Vol. 122, pp 16
Zurück zum Zitat Kumar A, Sebastian TM (2012) Machine learning assisted sentiment analysis. In: Proceedings of international conference on computer science and engineering (ICCSE’2012), pp 123–130 Kumar A, Sebastian TM (2012) Machine learning assisted sentiment analysis. In: Proceedings of international conference on computer science and engineering (ICCSE’2012), pp 123–130
Zurück zum Zitat Kwoh YS, Hou J, Jonckheere EA, Hayati S (1988) A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng 35(2):153–160CrossRefPubMed Kwoh YS, Hou J, Jonckheere EA, Hayati S (1988) A robot with improved absolute positioning accuracy for CT guided stereotactic brain surgery. IEEE Trans Biomed Eng 35(2):153–160CrossRefPubMed
Zurück zum Zitat Mann JA, MacDonald BA, Kuo I-H, Li X, Broadbent E (2015) People respond better to robots than computer tablets delivering healthcare instructions. Comput Hum Behav 43:112–117CrossRef Mann JA, MacDonald BA, Kuo I-H, Li X, Broadbent E (2015) People respond better to robots than computer tablets delivering healthcare instructions. Comput Hum Behav 43:112–117CrossRef
Zurück zum Zitat Martinello N, Loshak H (2020) Experiences with and expectations of robotic surgical systems: a rapid qualitative review Martinello N, Loshak H (2020) Experiences with and expectations of robotic surgical systems: a rapid qualitative review
Zurück zum Zitat McDermott H, Choudhury N, Lewin-Runacres M, Aemn I, Moss E (2020) Gender differences in understanding and acceptance of robot-assisted surgery. J Robot Surg 14:227–232CrossRefPubMed McDermott H, Choudhury N, Lewin-Runacres M, Aemn I, Moss E (2020) Gender differences in understanding and acceptance of robot-assisted surgery. J Robot Surg 14:227–232CrossRefPubMed
Zurück zum Zitat Meckl PH (1984) Minimizing residual vibration of a linear system using appropriately shaped forcing functions (Unpublished doctoral dissertation). Massachusetts Institute of Technology Meckl PH (1984) Minimizing residual vibration of a linear system using appropriately shaped forcing functions (Unpublished doctoral dissertation). Massachusetts Institute of Technology
Zurück zum Zitat Mejia C, Kajikawa, Y (2017) Assessing the sentiment of social expectations of robotic technologies. In: 2017 Portland international conference on management of engineering and technology (PICMET), pp 1–7 Mejia C, Kajikawa, Y (2017) Assessing the sentiment of social expectations of robotic technologies. In: 2017 Portland international conference on management of engineering and technology (PICMET), pp 1–7
Zurück zum Zitat Myers CG, Kudsi OY, Ghaferi AA (2018) Social media as a platform for surgical learning: use and engagement patterns among robotic surgeons. Ann Surg 267(2):233–235CrossRefPubMed Myers CG, Kudsi OY, Ghaferi AA (2018) Social media as a platform for surgical learning: use and engagement patterns among robotic surgeons. Ann Surg 267(2):233–235CrossRefPubMed
Zurück zum Zitat Pagani NR, Moverman MA, Puzzitiello RN, Menendez ME, Barnes CL, Kavolus JJ (2021) Online crowdsourcing to explore public perceptions of robotic-assisted orthopedic surgery. J Arthroplasty 36(6):1887–1894CrossRefPubMed Pagani NR, Moverman MA, Puzzitiello RN, Menendez ME, Barnes CL, Kavolus JJ (2021) Online crowdsourcing to explore public perceptions of robotic-assisted orthopedic surgery. J Arthroplasty 36(6):1887–1894CrossRefPubMed
Zurück zum Zitat Satava R, Bowersox J, Mack M, Krummel T (2001) Robotic surgery: state of the art and future trends. Contemp Surg 57(10):489–99 Satava R, Bowersox J, Mack M, Krummel T (2001) Robotic surgery: state of the art and future trends. Contemp Surg 57(10):489–99
Zurück zum Zitat Scoglio AA, Reilly ED, Gorman JA, Drebing CE (2019) Use of social robots in mental health and well-being research: systematic review. J Med Internet Res 21(7):e13322CrossRefPubMedPubMedCentral Scoglio AA, Reilly ED, Gorman JA, Drebing CE (2019) Use of social robots in mental health and well-being research: systematic review. J Med Internet Res 21(7):e13322CrossRefPubMedPubMedCentral
Zurück zum Zitat Sheetz KH, Claflin J, Dimick JB (2020) Trends in the adoption of robotic surgery for common surgical procedures. JAMA Netw Open 3(1):e1918911–e1918911CrossRefPubMedPubMedCentral Sheetz KH, Claflin J, Dimick JB (2020) Trends in the adoption of robotic surgery for common surgical procedures. JAMA Netw Open 3(1):e1918911–e1918911CrossRefPubMedPubMedCentral
Zurück zum Zitat Tang J, White CA, Arvind V, Cho S, Kim JS, Steinberger J (2022) What are patients saying about minimally invasive spine surgeons online: a sentiment analysis of 2,235 physician review website reviews. Cureus 14(4):e24113PubMedPubMedCentral Tang J, White CA, Arvind V, Cho S, Kim JS, Steinberger J (2022) What are patients saying about minimally invasive spine surgeons online: a sentiment analysis of 2,235 physician review website reviews. Cureus 14(4):e24113PubMedPubMedCentral
Zurück zum Zitat Zhang Y (2021) A big-data analysis of public perceptions of service robots amid COVID-19. Adv Hospitality Tourism Res (AHTR) 9(1):234–242CrossRef Zhang Y (2021) A big-data analysis of public perceptions of service robots amid COVID-19. Adv Hospitality Tourism Res (AHTR) 9(1):234–242CrossRef
Metadaten
Titel
Analysing public sentiment towards robotic surgery: an X (formerly Twitter) based study
verfasst von
Smriti Kumari
Anamika Sharma
Amit Chhabra
Ankit Gupta
Sarabjeet Singh
Ravi Verma
Publikationsdatum
01.12.2024
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2024
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-024-01226-9

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