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The purpose of this paper is to explore the relationship between subjective well-being (SWB) and exposure to online hate material using samples of Finnish and American youth and young adults. The authors aim to identify socio-demographic determinants of SWB and the social ties prevalent both online and offline that may be relevant to the discussion of how hate material associates with well-being.

The data are derived from online survey responses from both Finnish (n=555) and American (n=1,014) young people aged 15-30. The authors control for the possible effects of social trust, offline friendships, online victimisation and economic status, which have been found to associate with SWB in earlier studies.

The findings show a clear association that highlights the uniformity in how negatively intended material online affects young people, despite the inclusion of a cross-national comparison. The study confirms previous work concerning happiness and life satisfaction.

The survey used was not designed solely to address issues of SWB and as such a more targeted set of questions may have resulted in more in-depth data. Also, structural determinants of SWB, social spheres, and tie strength were analysed through proxy measures.

The findings concerning new variables linked to well-being and victimization in the cross-national context provide a new point of reference in terms of online hate being associated with happiness.

The authors consider a number of descriptive characteristics, determining the relationship between these variables and participants’ happiness. Through this cross-national data set, new comparisons were made possible between internet users of both countries. The study combines many earlier findings with new variables and theoretical frameworks to add new perspectives to the understanding of how well-being is affected online among young people.

Trust is one of the key elements in social interaction; however, few studies have analyzed how the proliferation of new information and communication technologies influences trust. The authors examine how exposure to hate material in the internet correlates with Finnish youths’ particularized and generalized trust toward people who have varying significance in different contexts of life. Hence, the purpose of this paper is to provide new information about current online culture and its potentially negative characteristics.

Using data collected in the spring of 2013 among Finnish Facebook users (n=723) ages 15-18, the authors measure the participants’ trust in their family, close friends, other acquaintances, work or school colleagues, neighbors, people in general, as well as people only met online.

Witnessing negative images and writings reduces both particularized and generalized trust. The negative effect is greater for particularized trust than generalized trust. Therefore, exposure to hate material seems to have a more negative effect on the relationships with acquaintances than in a more general context.

The study relies on a sample of registered social media users from one country. In future research, cross-national comparisons are encouraged.

The findings show that trust plays a significant role in online setting. Witnessing hateful online material is common among young people. This is likely to have an impact on perceived social trust. Hateful communication may then impact significantly on current online culture, which has a growing importance for studying, working life, and many leisure activities.

The prevalence of online hate material is a public concern, but few studies have analyzed the extent to which young people are exposed to such material. This study investigated the extent of exposure to and victimization by online hate material among young social media users.

The study analyzed data collected from a sample of Finnish Facebook users (n = 723) between the ages of 15 and 18. Analytic strategies were based on descriptive statistics and logistic regression models.

A majority (67%) of respondents had been exposed to hate material online, with 21% having also fallen victim to such material. The online hate material primarily focused on sexual orientation, physical appearance, and ethnicity and was most widespread on Facebook and YouTube. Exposure to hate material was associated with high online activity, poor attachment to family, and physical offline victimization. Victims of the hate material engaged in high levels of online activity. Their attachment to family was weaker, and they were more likely to be unhappy. Online victimization was also associated with the physical offline victimization.

While the online world has opened up countless opportunities to expand our experiences and social networks, it has also created new risks and threats. Psychosocial problems that young people confront offline overlap with their negative online experiences. When considering the risks of Internet usage, attention should be paid to the problems young people may encounter offline.

This study expands our knowledge about exposure to online hate material among users of the most popular social networking sites. It is the first study to take an in-depth look at the hate materials young people encounter online in terms of the sites where the material was located, how users found the site, the target of the hate material, and how disturbing users considered the material to be.

Several scholars have recently highlighted the narrowness of accounting research regarding it as a threat to scholarly developments in the field. The aim of this study was to chart progress in management accounting research using a sample of doctoral dissertations published in Finland. In particular, the study examines the range and diversity of research strategic choices in Finnish dissertations over time, including the topics and methodological and theoretical approaches chosen. The authors also briefly compare findings over time and with other progress studies.

A longitudinal historical investigation was selected. All of the 80 management accounting doctoral dissertations published in Finnish business schools and departments during 1945-2015 were analysed.

The findings reveal that an expansion of doctoral education has led to an increasing diversity of research strategic choices in Finland. Different issues have been of interest at different times; so, it has been possible to cover a wide range of cost, management accounting and other topics and to use different methodological and theoretical approaches over time. Consequently, management accounting has become a rich and multifaceted field of scientific research.

While this analysis is limited to doctoral research in Finland, the results should be relevant in advancing the understanding of the development of management accounting research.

Overall, the findings support the view that there have been, and continue to be, many ways to conduct innovative research in the field of management accounting.

Dissertation research in this field has been extensive and vital enough to educate new generations of academics, guarantee continuity of the subject as an academic discipline and make management accounting a significant academic field of research.

The paper contributes to current research on management accounting change by an analysis of a sample of doctoral dissertations.

This study analyses how the implementation of PPPs to operate rural water infrastructures and deliver water to local population has led to a new accountability archetype.

The archetype theory is used to analyse the process of implementing PPPs as a new archetype and setting up systems and structures of accountability between contracting parties. The empirical part of the study is based on extensive document analysis in an East African country. Documents analysed are from governmental sources, UNICEF and the World Bank and cover a period from 1998 to early 2019.

The process of implementing PPPs was revolutionary at the national level and evolutionary at micro levels. The sequence of the change process moved from central to peripheral. The linearity followed a reorientation track strategy. Setting up systems and structure of accountability was evolutionary, peripheral to central following the reorientation strategy. National authorities reacted proactively to comments and suggestions from international donors and local population. However, not all districts have fully implemented PPPs in their rural water sector. The structure of accountability at the local level, however, still suffers from logistical and professional capacity constraints.

Empirical findings cannot be generalised to other situations, but the theoretical framework used in this study can be applied elsewhere.

Giving priority to hearing from end users themselves before designing and implementing policies that intend to respond to specific local needs is recommended.

This study explains the ways in which micro-organisational change can lead to revolutionary archetypes such as PPPs, whereas the implementation of systems and the structure of accountability at inter-organisational level remain evolutionary.

Hate speech in recent times has become a troubling development. It has different meanings to different people in different cultures. The anonymity and ubiquity of the social media provides a breeding ground for hate speech and makes combating it seems like a lost battle. However, what may constitute a hate speech in a cultural or religious neutral society may not be perceived as such in a polarized multi-cultural and multi-religious society like Nigeria. Defining hate speech, therefore, may be contextual. Hate speech in Nigeria may be perceived along ethnic, religious and political boundaries. The purpose of this paper is to check for the presence of hate speech in social media platforms like Twitter, and to what degree is hate speech permissible, if available? It also intends to find out what monitoring mechanisms the social media platforms like Facebook and Twitter have put in place to combat hate speech. Lexalytics is a term coined by the authors from the words lexical analytics for the purpose of opinion mining unstructured texts like tweets.

This research developed a Python software called polarized opinions sentiment analyzer (POSA), adopting an ego social network analytics technique in which an individual’s behavior is mined and described. POSA uses a customized Python N-Gram dictionary of local context-based terms that may be considered as hate terms. It then applied the Twitter API to stream tweets from popular and trending Nigerian Twitter handles in politics, ethnicity, religion, social activism, racism, etc., and filtered the tweets against the custom dictionary using unsupervised classification of the texts as either positive or negative sentiments. The outcome is visualized using tables, pie charts and word clouds. A similar implementation was also carried out using R-Studio codes and both results are compared and a t-test was applied to determine if there was a significant difference in the results. The research methodology can be classified as both qualitative and quantitative. Qualitative in terms of data classification, and quantitative in terms of being able to identify the results as either negative or positive from the computation of text to vector.

The findings from two sets of experiments on POSA and R are as follows: in the first experiment, the POSA software found that the Twitter handles analyzed contained between 33 and 55 percent hate contents, while the R results show hate contents ranging from 38 to 62 percent. Performing a t-test on both positive and negative scores for both POSA and R-studio, results reveal p-values of 0.389 and 0.289, respectively, on an α value of 0.05, implying that there is no significant difference in the results from POSA and R. During the second experiment performed on 11 local handles with 1,207 tweets, the authors deduce as follows: that the percentage of hate contents classified by POSA is 40 percent, while the percentage of hate contents classified by R is 51 percent. That the accuracy of hate speech classification predicted by POSA is 87 percent, while free speech is 86 percent. And the accuracy of hate speech classification predicted by R is 65 percent, while free speech is 74 percent. This study reveals that neither Twitter nor Facebook has an automated monitoring system for hate speech, and no benchmark is set to decide the level of hate contents allowed in a text. The monitoring is rather done by humans whose assessment is usually subjective and sometimes inconsistent.

This study establishes the fact that hate speech is on the increase on social media. It also shows that hate mongers can actually be pinned down, with the contents of their messages. The POSA system can be used as a plug-in by Twitter to detect and stop hate speech on its platform. The study was limited to public Twitter handles only. N-grams are effective features for word-sense disambiguation, but when using N-grams, the feature vector could take on enormous proportions and in turn increasing sparsity of the feature vectors.

The findings of this study show that if urgent measures are not taken to combat hate speech there could be dare consequences, especially in highly polarized societies that are always heated up along religious and ethnic sentiments. On daily basis tempers are flaring in the social media over comments made by participants. This study has also demonstrated that it is possible to implement a technology that can track and terminate hate speech in a micro-blog like Twitter. This can also be extended to other social media platforms.

This study will help to promote a more positive society, ensuring the social media is positively utilized to the benefit of mankind.

The findings can be used by social media companies to monitor user behaviors, and pin hate crimes to specific persons. Governments and law enforcement bodies can also use the POSA application to track down hate peddlers.