Evaluating security and privacy issues of social networks based information systems in Industry 4.0
[EN] The present study aimed to analyse the main risks related to security and privacy of social networks based information systems in Industry 4.0. The methodology we used is an innovative exploratory data-driven process divided into three steps. First, we performed sentiment analysis to divide the database composed of 67, 206 tweets into feelings. Second, we applied a topic-modelling algorithm to extract topics. Third, we applied textual analysis to collect insights. A total of 10 topics related to security and privacy issues were identified as results. The paper concludes with a discussion of the challenges and main concerns related to the identified topics.
Exploring the challenges of remote work on Twitter users’ sentiments: From digital technology development to a post-pandemic era
The boost in the use and development of technology, spurred by COVID-19 pandemic and its consequences, has sped up the adoption of new technologies and digital platforms in companies. Specifically, companies have been forced to change their organizational and work structures. In this context, the present study aims to identify the main opportunities and challenges for remote work through the use of digital technologies and platforms based on the analysis of user-generated content (UGC) in Twitter. Using computer-aided text analysis (CATA) and natural language processing (NLP), in this study, we conduct a sentiment analysis developed with Textblob, which works with machine learning. We then …
From user-generated data to data-driven innovation: A research agenda to understand user privacy in digital markets
Abstract In recent years, strategies focused on data-driven innovation (DDI) have led to the emergence and development of new products and business models in the digital market. However, these advances have given rise to the development of sophisticated strategies for data management, predicting user behavior, or analyzing their actions. Accordingly, the large-scale analysis of user-generated data (UGD) has led to the emergence of user privacy concerns about how companies manage user data. Although there are some studies on data security, privacy protection, and data-driven strategies, a systematic review on the subject that would focus on both UGD and DDI as main concepts is lacking. There…