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The purpose of this paper is to explore the reaction of Pakistani citizens toward online privacy in the context of the Pakistan Government's COVID-19 app privacy breach.

The authors implemented supervised and unsupervised machine learning methods, that is, topic modeling and sentiment analysis on Google app store user review data.

There was no visible concern shown by the citizens toward the COVID-19 app privacy breach, even though it was well highlighted in the news. Other studies have also indicated that concern for online privacy remains low in developing countries, which aligns with the findings of this paper.

Globally COVID-19 apps have been a cause of concern in terms of public privacy. To the best of the authors’ knowledge, this paper is the first in the Pakistani context to show the impact of a well-document privacy breach of a government COVID-19 app.

The present study distinguishes itself by pioneering an innovative framework that integrates key elements of prospect theory and the fundamental principles of electronic word of mouth (EWOM) to forecast Bitcoin/USD price fluctuations using Twitter sentiment analysis.

We utilized Twitter data as our primary data source. We meticulously collected a dataset consisting of over 3 million tweets spanning a nine-year period, from 2013 to 2022, covering a total of 3,215 days with an average daily tweet count of 1,000. The tweets were identified by utilizing the “bitcoin” and/or “btc” keywords through the snscrape python library. Diverging from conventional approaches, we introduce four distinct variables, encompassing normalized positive and negative sentiment scores as well as sentiment variance. These refinements markedly enhance sentiment analysis within the sphere of financial risk management.

Our findings highlight the substantial impact of negative sentiments in driving Bitcoin price declines, in contrast to the role of positive sentiments in facilitating price upswings. These results underscore the critical importance of continuous, real-time monitoring of negative sentiment shifts within the cryptocurrency market.

Our study holds substantial significance for both risk managers and investors, providing a crucial tool for well-informed decision-making in the cryptocurrency market. The implications drawn from our study hold notable relevance for financial risk management.

We present an innovative framework combining prospect theory and core principles of EWOM to predict Bitcoin price fluctuations through analysis of Twitter sentiment. Unlike conventional methods, we incorporate distinct positive and negative sentiment scores instead of relying solely on a single compound score. Notably, our pioneering sentiment analysis framework dissects sentiment into separate positive and negative components, advancing our comprehension of market sentiment dynamics. Furthermore, it equips financial institutions and investors with a more detailed and actionable insight into the risks associated not only with Bitcoin but also with other assets influenced by sentiment-driven market dynamics.

The purpose of this paper is to explore the effect of Elon Musk’s Twitter bio change on January 29, 2021 on the discourse around Bitcoin (BTC) on Twitter and to understand how these changes relate to the changes in Bitcoin price around that time.

This study implements sentiment analysis and text mining on Twitter data to explore changes in public sentiments toward Bitcoin after Elon Musk’s Twitter bio change. Furthermore, it uses Bitcoin price data obtained from the Binance exchange to understand its relation with Twitter discussion.

Elon Musk’s bio change on Twitter on January 29 increased the tweet volume mentioning Bitcoin. This increase in tweets had a strong positive correlation with Bitcoin price and preceded the rise in Bitcoin price. Although the bio change had an apparent effect on the tweet volume, there was no considerable effect on the tweet sentiments, indicating that tweet sentiment is a poor predictor of Bitcoin price.

This paper proposes an understanding of how social media influencers, like Elon Musk, affect the discourse around Bitcoin and can, in turn, have an impact on Bitcoin price.

This paper examines the role of co-inventor collaboration with China and/or the USA on a country's increase in centrality in global knowledge networks. It also explores the role of specific institutional factors – corruption and intellectual property rights (IPR) protection – on this relationship.

In the study, co-inventor data from the United States Patent and Trademark Office (USPTO) applications have been used to construct networks of technological knowledge collaboration at the country level over the years 2002–2015. Using eigenvector centrality as the dependent variable, the study uses fixed effect regression analyses on a panel of 171 countries, contributing to recent debates on knowledge networks and international cooperation.

Building on research in economic development, innovation and social network theory, this research finds that co-patenting with Chinese inventors is positively related to a country's centrality in global knowledge networks and that this relationship is negatively moderated by collaboration with the current most central knowledge network – namely that of the USA – suggesting a substitution effect. It also finds a partial substitution between institutional factors, IPRs protection and transparency, and collaboration with China on a country's knowledge centrality.

Regarding policymakers, the findings can be used to encourage international collaboration for increased access to new sources of knowledge that fosters innovation while keeping a close eye on local institutions, especially emerging economies that want to increase their international knowledge network centrality.

This study creates a unique panel data set and extends the social networks approach in international business literature, focusing on institutional characteristics related to participation in knowledge networks.

Through increasing globalization, cities are becoming increasingly interconnected with each other. To remain competitive, it is necessary for cities to combine complementary non-local sources of knowledge with local knowledge sources. The authors contend that an increase in non-local knowledge sourcing tends to enhance local knowledge sourcing too. The purpose of this study is to examine the influence of international knowledge sources on the capacity to build upon local knowledge sources in a city region. In addition, the authors investigate whether information and communication technologies (ICT) knowledge sources have a bigger impact than do other fields of knowledge on local knowledge connectivity.

Using the US Patent and Trademark Office data, the authors study knowledge sourcing trends for the years 1980-2016 across 33 global cities. Backward patent citations from these granted patents are used to identify the location of inventors of prior knowledge sources, and the geography of knowledge building connections over time is assessed by using the inventor locations of cited (source) and citing (recipient) patents.

The authors show that international knowledge sourcing is highly connected with local knowledge sourcing. The authors also find that ICT have a significant effect on this relationship. However, there are significant differences across cities in the extent and nature of this relationship.

This study contributes to the literature on the changing geography of knowledge connections. It provides a detailed picture of changing knowledge sourcing trends at a city region level, and it improves our understanding of the role played by a variety of knowledge connections in helping a city remain competitive.

Although there is a growing body of work on immigrants' information behavior, little is known about the pre-arrival information experiences of immigrants who consult formal information sources such as immigration agents. Drawn from a larger study on the information behavior of immigrants, this paper mainly reports the semi-structured interview findings on the pre-arrival information experiences of Bangladeshi immigrants who used formal information sources with discussion on how that affected their post-arrival settlement into Canada.

The study used a mixed method approach with semi-structured interviews (n = 60) and surveys (n = 205) with participants who arrived in Canada between the years of 1971 and 2017. Data were collected from May 2017 to February 2018.

Although the overall scope of the original study is much larger, this paper features findings on the pre-arrival information experiences derived mainly from an analysis of interview data. This study provides insights into the pre-arrival information experiences of Bangladeshi immigrants consulting formal information sources such as immigration firms, individual immigration consultants and more formal government agencies. The author introduces a new concept of “information crafting” by exploring the negative consequences of selective information sharing by immigration consultants/agents in newcomers' settlements in Canada, primarily positive information about life in Canada, sometimes with exaggeration and falsification. The interview participants shared story after the story of the settlement challenges they faced after arriving in Canada and how the expectations they built through the information received from immigration consultants and government agencies did not match after arrival. This study emphasizes the importance of providing comprehensive information about life in Canada to potential newcomers so that they can make informed decisions even before they apply.

The findings of this study have theoretical and practical implications for policy and research. This study provides insights into the complicated culturally situated pre-arrival information experiences of Bangladeshi immigrants. Moreover, the study findings encourage researchers in various disciplines, including psychology, migration studies and geography, to delve more deeply into newcomers' information experiences using an informational lens to examine the information newcomers receive from diverse sources and their effects on their post-arrival settlement in a new country. The study challenges the general assumptions that formal information sources are always reputable, useful, and comprehensive, and it provides some future directions for research that seeks to understand the culturally situated information behavior of diverse immigrant groups.

This study aims to explore how factors such as working conditions, lifestyle choices and demographic characteristics may affect the mental health of industrial workers in Kuwait.

Within the scope of the study’s objective, the authors reached 400 industrial workers (228 male, 172 female) working in oil and gas organizations in Kuwait. An ordered logistic regression model was conducted to examine the effect of relevant independent variables on workers’ mental health.

Result indicated that employees with a lower education level (p-value = 0.015), employees who were smokers (p-value = 0.004) and employees with night shifts (p-value = 0.019), were more likely to experience mental health issues. Furthermore, result strongly highlights a higher chance of experiencing mental health problems among the workers who had longer working times (p-value = 0.000). On the other hand, having children (p-value = 0.042), visiting a mental health professional (p = 0.014) and living in a house with others (flat mate, family members, etc.) (p-value = 0.016) were statistically significant factors to improve employees’ mental health. Surprisingly, the authors’ research did not find a significant relationship between the mental health issues experienced by employees and their yearly income.

The paper lies in its exploration of the impact of working conditions, lifestyle choices and demographic factors on mental health of industrial workers using statistical approach. By applying ordered logistic regression, this study uncovers new insights into mental health of industrial workers.

This study aims to examine whether the financial market rewards the sustainable companies by investigating the impact of sustainability assurance levels on market capitalization of the CAC 40 firms. This analysis is complemented by examining the role of company characteristics to investors, providing a clearer picture of the functioning of the capital market.

To analyze the effect of sustainability assurance levels on market capitalization for the period 2011–2021, this study used a simplified version of the linear information model which is based on Ohlson model (1995) and Crouse (2007). This model is a multiple linear regression model which will be applied to panel data.

The study found that sustainability assurance levels negatively impact market capitalization. Higher investment decisions occur when sustainability reports have limited assurance, likely due to resource waste and costs exceeding income. In addition, net income, corporate social responsibility (CSR) indexes, leverage and performance significantly influence market capitalization.

This study offers valuable insights for both companies and investors, providing guidance on making investment decisions based on varying levels of sustainability assurance.

The current study sheds light on a relatively unexplored area regarding the connection between sustainability assurance and market reaction. Hence, this research focuses on a novel aspect of sustainability assurance by investigating how firm visibility in terms of sustainability practices impacts market capitalization.

The purpose of this paper is to investigate the potential influence of corporate governance mechanisms on risk disclosure quality in Tunisia.

The authors examine 152 annual reports of Tunisian non-financial-listed firms during 2008–2013, and use the manual content analysis method to measure the risk disclosure quality.

The authors find that the quality of risk disclosure in Tunisian companies is relatively low, and also find that the quality of risk disclosure is positively associated with institutional ownership, board independence, the presence of women on the board, the presence of family members on the board and the independence of audit committee. Managerial ownership has a negative effect on risk disclosure quality. Finally, the authors find that the revolution decreases the influence of concentration ownership, government ownership, family ownership and audit committee size on risk disclosure quality.

Using a comprehensive set of corporate governance mechanisms and a new measure for risk disclosure quality in Tunisia, the authors provide the first empirical evidence on the impact of corporate governance mechanisms on risk disclosure quality in a developing country. The study has theoretical and practical implications for both developed and developing countries.