Search results

The present chapter has reviewed the opportunities and limitations of the Russian Federation to situate as a leading international destination. There are significant methodological and conceptual issues during the assessment of the world countries and regions safety level. They are caused by lack of the universal assessment method of such risks, incompleteness of the risk criteria taken into consideration, subjective assessment factors, and occasional substitution of the risk factors with the political–competitive ones. Still, the safety issue is one of the most important for a modern tourist. The available information resources, providing their own safety level assessment of the world countries and regions for travellers, differ between them in terms of the selected categories, specified safety levels of the countries and regions and also in terms of understanding and details of the travel risk notion itself. But the greatest challenge for an ordinary tourist, who does not have experience in searching specialised information, is to become familiar with these information resources.

Purpose — This chapter investigates how dishonesty may be legitimized in organizations through customary practices of gift giving, patronage, and non-meritocratic employment practices.Design/methodology/approach — A survey of managers was undertaken in four sub-Saharan African countries: Ghana, Kenya, Tanzania, and Uganda.Findings — Gift giving was perceived to be widespread in organizations in all four countries and yet the vast majority of managers we surveyed, rejected the proposition that the practice of gift giving causes dishonesty in organizations. There were cross-country variations as to whether the expectations of the society on individuals “glorify and endorse” dishonesty as they may feel pressured to accumulate and (re)distribute wealth among their wider social groups. Non-meritocratic employment practices were unanimously perceived to engender incompetent workforce, lack of accountability and transparency without necessarily improving trust, and loyalty in organizations.Research limitations — This study used quantitative methods to gauge managers’ perceptions of the relationship between customary practices and dishonest behavior in only four African countries. Further qualitative research is required to gain a deeper insight into how customary practices may inform dishonest behavior in organizations.Implications for managers — Managers should be clear about the distinction between customary practices and dishonest behavior in order to facilitate the development of appropriate organizational strategies to minimize their negative impacts.Originality/value — This paper explores the relationship between dishonesty and customary practices of gift giving, patronage and nepotism in African organizations from the managers’ point of view, an approach that had not been undertaken previously.

After the ex-National Security Agency contractor Edward Snowden¹ disclosures of the National Security Agency surveillance of Americans’ online and phone communications, the Pew Research Center² administrated a panel survey to collect data concerning Americans’ opinions about privacy and security. This survey has mixed types of qualitative questions (closed and open-ended). In this context, to our knowledge, until today, no research has been applied on the open-ended part of these data. In this chapter, first the authors present their findings from applying sentiment analysis and topic extraction methods; second, the authors demonstrate their analysis to sentiments polarities; and finally, the authors interpret the semantic relationships between topics and their associated negativity, positivity, and neutral sentiments.

Purpose – This chapter examines how sentiment analysis and web-crawling technology can be used to conduct large-scale data analyses of extremist content online.

Methods/approach – The authors describe a customized web-crawler that was developed for the purpose of collecting, classifying, and interpreting extremist content online and on a large scale, followed by an overview of a relatively novel machine learning tool, sentiment analysis, which has sparked the interest of some researchers in the field of terrorism and extremism studies. The authors conclude with a discussion of what they believe is the future applicability of sentiment analysis within the online political violence research domain.

Findings – In order to gain a broader understanding of online extremism, or to improve the means by which researchers and practitioners “search for a needle in a haystack,” the authors recommend that social scientists continue to collaborate with computer scientists, combining sentiment analysis software with other classification tools and research methods, as well as validate sentiment analysis programs and adapt sentiment analysis software to new and evolving radical online spaces.

Originality/value – This chapter provides researchers and practitioners who are faced with new challenges in detecting extremist content online with insights regarding the applicability of a specific set of machine learning techniques and research methods to conduct large-scale data analyses in the field of terrorism and extremism studies.

The purpose of this study is to determine which quantitative metrics are most representative of investor sentiment in the US equity markets. Sentiment is the aggregation of consumers', investors', and producers' thoughts and opinions about the future of the financial markets. By analyzing the change in popular economic indicators, financial market statistics, and sentiment reports, we can gain information on investor reactions. Furthermore, we will use machine learning techniques to develop predictive models that will attempt to forecast whether the stock market will go up or down based on the percent change in these indicators.

Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.

Terrorist events are unforeseen and have the potential to shake and rattle markets and investors. The purpose of this study is to examine whether major terrorist incidents have affected the Economic Sentiment Indicator (ESI) in four European countries.

An index is constructed that weights the severity of each event and then used to evaluate through the use of vector autoregressive and impulse response analysis estimation techniques whether or not and to what extent the ESI has been affected.

Effects were more pronounced and evident in the case of France and Germany while the ESI in Spain and Great Britain did not appear to be particularly affected by terrorist incidents.

The effects of terrorism on economic sentiment in other countries will provide additional evidence that will allow more robust and conclusive statistical inferences.

The impact of terrorist activity on the ESI for the four European countries studied here has not been examined before using VAR and impulse response analysis.