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Cannabis use continues to increase worldwide, and a number of nation states are changing their cannabis policies. Policy changes require research into key populations, namely, people who use cannabis. This study aims to examine sociodemographic differences of young Finns who reported using cannabis mainly for self-medication versus mainly recreationally, as well as their reported effects of cannabis use.

The data come from an anonymous online survey (N = 247, 70.0% males, 25.9% females, 4.1% other) that was analysed using multiple logistic regression. The authors focused on whether various demographic indicators differed between those who reportedly used cannabis mainly for recreational purposes and mainly for self-medicinal purposes. The authors also qualitatively examined the respondents’ experienced effects of cannabis, both desired and undesired.

Being older and female, living in a smaller city and earlier age of initiation of cannabis use were statistically significant in predicting the medicinal use of cannabis. The majority of recreational effects were related to themes such as relaxation and pleasure, but many participants also reported desired medical effects. Similarly, many participants reported several undesired effects.

Understanding especially young people’s motivations to use cannabis, which include using it for various medical effects, can improve the design of harm reduction and treatment programmes as well as enhance the well-being of people who use cannabis.

This study gives a nuanced account of sociodemographic factors and motivations of young people who use cannabis in Finland as well as the reported effects it has on them, which complements data from national drug surveys.

Social media platforms are increasingly used at work to facilitate work-related activities and can either challenge or make people feel more productive at jobs. This study drew from technostress and employee well-being literature and analyzed longitudinal effects of professional social media (PSM) invasion, work engagement and work exhaustion on PSM-enabled productivity.

Nationally representative five-wave survey data of Finnish employees were analyzed with hybrid multilevel linear regression analysis. Outcome measure was PSM-enabled productivity and the predictors included PSM invasion, work exhaustion and work engagement. Age, gender, education, occupational sector, managerial position, remote work and personality traits were used as control variables.

PSM invasion and work engagement had both within-person and between-person effects on PSM-enabled productivity. Higher educated and individuals with open personality reported higher PSM-enabled productivity. No association between work exhaustion and PSM-enabled productivity was found.

The findings are central considering the increasing use of social media and other technologies for work purposes. The authors challenge the dominant view in the literature that has often seen PSM invasion as a negative factor. Instead, PSM invasion's positive association with PSM-enabled productivity and the association of work engagement and PSM-enabled productivity should be recognized in work life.

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.

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.

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.

Through the prism of intimacy, this chapter discusses how experiences of pain and loss in relation to bereavement by suicide is expressed in the black metal music and lyrics by Danish band Orm. Orm's 2019-album Ir ‘verdigris’, entangles the emotional complex and personal relations to the local, natural surroundings of the island Bornholm, including a named tree and lake, as well as local folklore and Norse mythology. As part of fieldwork, the author muddles with intimacy to define an approach sensitive enough to deal with strong and unspeakable emotions, including the idea of cultural intimacy and public embarrassment related to the issue of suicide. The author also reflects on how my participation in the pain of others informs the interpretation. The chapter suggests that Orm's black metal is doing important pain work, opening to listeners a path towards disembarrassment.

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.