Bibliographic Details
Title: |
Web 3.0 Adoption Behavior: PLS-SEM and Sentiment Analysis |
Authors: |
Hizam, Sheikh M., Ahmed, Waqas, Akter, Habiba, Sentosa, Ilham, Masrek, Mohamad N. |
Source: |
15th International Baltic Conference on Digital Business and Intelligent Systems (DB&IS), July 03-06, 2022, University of Latvia, Riga, Latvia |
Publication Year: |
2022 |
Collection: |
Computer Science |
Subject Terms: |
Computer Science - Computers and Society, Computer Science - Human-Computer Interaction |
More Details: |
Web 3.0 is considered as future of Internet where decentralization, user personalization and privacy protection would be the main aspects of Internet. Aim of this research work is to elucidate the adoption behavior of Web 3.0through a multi-analytical approach based on Partial Least Squares Structural Equation Modelling (PLS-SEM) and Twitter sentiment analysis. A theoretical framework centered on Performance Expectancy (PE), Electronic Word-of-Mouth (eWOM) and Digital Dexterity (DD), was hypothesized towards Behavioral Intention (INT) of the Web 3.0 adoption. Surveyed data were collected through online questionnaires and 167 responses were analyzed through PLS-SEM. While 3,989 tweets of Web3 were analyzed by VADER sentiment analysis tool in RapidMiner. PLS-SEM results showed that DD and eWOM had significant impact while PE had no effect on INT. Moreover, these results were also validated by PLS-Predict method. While sentiment analysis explored that 56% tweets on Web 3.0 were positive in sense and 7% depicted negative sentiment while remaining were neutral. Such inferences are novel in nature and an innovative addition to web informatics and could support the stakeholders towards web technology integration Comment: 14 pages, 4 figures, 5 tables, 15th International Baltic Conference on Digital Business and Intelligent Systems (DB&IS),July 03-06, 2022, University of Latvia, Riga, Latvia |
Document Type: |
Working Paper |
Access URL: |
http://arxiv.org/abs/2209.04900 |
Accession Number: |
edsarx.2209.04900 |
Database: |
arXiv |