Title: Understanding the Industry 4.0 Revolution Using Twitter Analytics

Author (s):: Bedi J.; Padhy R.K.; Padhi S.S.

Journal: Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications

Month and Year: NA 2021

Abstract: Social media (SM) data provide a vast record of everyday thoughts, feelings, and actions of humans at a resolution previously unimaginable. Because user behavior on SM reflects events in the real world, researchers have realized that they can use SM to forecast and make predictions. To grasp the context, this study focuses on Twitter as one of the social networking sites to improve our understanding of the fourth industrial revolution and its associated initiatives in the context of SM. These tweets were collected using the hashtags #Industry4.0, #factoroffuture, and #AdvanceManufacturing followed by Twitter analytics that comprises three types of analytics, namely, descriptive statistics, content analytics that includes sentiment analytics and emotional score analysis, and network analysis and topic modeling. This methodology is applied to around 31,000 tweets to answer four research questions: (1) Which tweets characterize Industry 4.0? The finding suggests that a great part (35%) of #Industry4.0 tweets contains more than one hashtag. Primarily, tweets about the convenient issues and difficulties with Industry 4.0 applications are high in numbers. (2) What are the topics shared on Twitter? Findings suggest that most mainstream hashtags are like themed territories canvassed in scholarly diaries. They incorporate #IOT, #IIOT, #Bigdata, #Analytics, #Cybersecurity, #Innovation, #Automation, #digital, #sensors, #cyberattacks, #smart city, #Block chain, #5G, #drone, #robotics, #RPA, #ML, #deep learning, #cloud, and #AI. Few noticeable ones were #PlanetEarthFirst, #SustainableDevelopment, and #Futureofwork. (3) What are the features of the users who use Industry 4.0-related tweets? Findings suggest that some of the clients are unemployed, while others are professionals. Almost all the tweets under this group of clients are unique and are expert in innovation-related jobs. Lastly, (4) What are the sentiments of these tweets? Findings suggest that the tweet data test for #Industry4.0 consists of moderately positive feeling emphasizing occasions, fabricating capacity news, business use case, changes, reports, innovations, abilities, and administration notices. Finally, the future scope and limitations of the study are also reported. © 2022 selection and editorial matter, Shivani Bali, Sugandha Aggarwal, Sunil Sharma; individual chapters, the contributors.

Document Type: Book chapter

DOI: https://doi.org/10.1201/9781003140474-1