The educational system in Sweden is expanding and while some see higher education as a remedy for unemployment, others argue that credentialing of the society with diplomas will harm the competition on the labour market and the value of higher education. However, the effects of educational expansion are noticeable not only at the macro, but also at the micro level. Studies have shown that Sweden is internationally on the bottom of the list when it comes to gross returns of higher education. During the 1990s the educational expansion led to the impairment of university and college degrees to uplift individuals to high income positions. Studies have also shown that fluctuations in training premia are inconsistent with the supply of higher educated labour force. The focus of this quantitative dissertation is on the period between 2000 and 2010. By measuring the success on the labour market in terms of monthly salary the aim is to find out how the educational expansion affected Swedish labour market after the 1990s. By using SPSS, a multiple linear regression analysis is applied on data that is extracted from Levnadsnivåundersökningen (LNU) 2000 and 2010. The results suggest that even though the effects of higher education are not dramatically different between these years, it explained more of the total variance in monthly salary in 2000. Furthermore, social background and social networks had stronger effects on the success on the labour market in 2010. This implies that meritocratic principles were utilized more during the early twenty first century and that social status continues to determine salaries in a modern capitalist society.

Keeping forestland intact has emerged as a critical policy objective at state and federal levels. This target has been supported by substantial public investment. The collective impact from the bequest decisions of millions of landowning individuals and families has the potential to affect the extent and functionality of future forests in the United States. Despite a growing body of research devoted to studying these transitions in forest ownership, much remains unknown about how family forest owners make decisions in this arena. The social and emotional dimensions of woodland succession planning have been particularly under-examined. This thesis explores the process of planning for the future use and ownership of woodlands through in-depth analysis of 32 semi-structured interviews with family forest owners in Massachusetts, Maine, New York, and Vermont. The first article investigates how family forest owners evaluate and integrate stories derived from their social networks when planning for the future of their woodlands. Analysis of the themes contained in stories framed as “cautionary tales” revealed common fears surrounding succession planning. The second article explores the complexity of emotional relationships with family forests showing how emotional geographies manifest in the succession planning process. Together, these studies deepen understanding of how family forest owners plan for the future of private woodlands and offer implications for Extension and outreach.

Då de äldre delarna av populationen förväntas bli en större andel av den svenska totalpopulationen är det av intresse att undersöka deras hälsotillstånd, där livstillfredsställelse tycks vara en viktig faktor för ett gott åldrande. Utomlands har ett starkt stöd för en korrelation mellan livstillfredsställelse och religiositet hittats. Ett delsyfte i denna studie var att undersöka om en sådan korrelation även kan hittas i sekulära Sverige. Utifrån att också en stark korrelation mellan livstillfredsställelse och sociala nätverk hittats både utomlands och i Sverige var nästa delsyfte att undersöka om de sociala nätverk som kan hittas via ett religiöst deltagande i till exempel en församling bättre kan förklara religionens effekt på livstillfredsställelse än just religiositeten själv. Deltagarna i studien var hämtade från en longitudinell studie kring åldrande och vård kallad "The Swedish National Study on Aging and Care" (SNAC). Resultaten kunde inte visa på någon korrelation mellan religiositet och livstillfredsställelse i Sverige. I och med detta utgick ansatsen till att förklara en sådan korrelation. Studien pekade på att effekten religiositet har på en svensk befolkning tycks skilja sig från den effekt den har på andra populationer. / As the elder parts of the population are expected to become a larger proportion of the Swedish total population there is an interest in investigating their state of health, for which life satisfaction seems to be an important factor. Strong support for a correlation between life satisfaction and religiousness has been found outside of Sweden. One aim of this study was to investigate if such a correlation could also be found in secular Sweden. A strong correlation between life satisfaction and social networks has also been found both in and outside of Sweden. Following this the next aim of the study was to investigate if the social network that can be found via religious participation in for example a congregation could better explain the effect of religion on life satisfaction than religiousness itself. The participants in the study were gathered from a longitudinal study about aging and care called "The Swedish National Study on Aging and Care"(SNAC). The results did not show any correlation between religiousness and life satisfaction in Sweden. The Study indicates that the effect religiousness has on the Swedish population seems to be different from the effect it has on other populations.

Large scale social data from online social networks, instant messaging applications, and wearable devices have seen an exponential growth in a number of users and activities recently. The rapid proliferation of social data provides rich information and infinite possibilities for us to understand and analyze the complex inherent mechanism which governs the evolution of the new technology age. Influence, as a natural product of information diffusion (or propagation), which represents the change in an individual’s thoughts, attitudes, and behaviors resulting from interaction with others, is one of the fundamental processes in social worlds. Therefore, influence analysis occupies a very prominent place in social related data analysis, theory, model, and algorithms. In this dissertation, we study the influence analysis under the scenario of big social data. Firstly, we investigate the uncertainty of influence relationship among the social network. A novel sampling scheme is proposed which enables the development of an efficient algorithm to measure uncertainty. Considering the practicality of neighborhood relationship in real social data, a framework is introduced to transform the uncertain networks into deterministic weight networks where the weight on edges can be measured as Jaccard-like index. Secondly, focusing on the dynamic of social data, a practical framework is proposed by only probing partial communities to explore the real changes of a social network data. Our probing framework minimizes the possible difference between the observed topology and the actual network through several representative communities. We also propose an algorithm that takes full advantage of our divide-and-conquer strategy which reduces the computational overhead. Thirdly, if let the number of users who are influenced be the depth of propagation and the area covered by influenced users be the breadth, most of the research results are only focused on the influence depth instead of the influence breadth. Timeliness, acceptance ratio, and breadth are three important factors that significantly affect the result of influence maximization in reality, but they are neglected by researchers in most of time. To fill the gap, a novel algorithm that incorporates time delay for timeliness, opportunistic selection for acceptance ratio, and broad diffusion for influence breadth has been investigated. In our model, the breadth of influence is measured by the number of covered communities, and the tradeoff between depth and breadth of influence could be balanced by a specific parameter. Furthermore, the problem of privacy preserved influence maximization in both physical location network and online social network was addressed. We merge both the sensed location information collected from cyber-physical world and relationship information gathered from online social network into a unified framework with a comprehensive model. Then we propose the resolution for influence maximization problem with an efficient algorithm. At the same time, a privacy-preserving mechanism are proposed to protect the cyber physical location and link information from the application aspect. Last but not least, to address the challenge of large-scale data, we take the lead in designing an efficient influence maximization framework based on two new models which incorporate the dynamism of networks with consideration of time constraint during the influence spreading process in practice. All proposed problems and models of influence analysis have been empirically studied and verified by different, large-scale, real-world social data in this dissertation.

The politicians have entered a new platform with the potential to democratization and to exchange ideas. Therefore, we want to look into what new conditions social media creates for politicians. Through strategic political communication the goal-oriented two-way communication is depicted as it is crucial for relations to establish, build up, maintain and to be affected.   One aspect of this is about the creation of messages and the visual communication affecting the meaning of the content. In our study, these theories have become the foundation in the research, and of the tools used when developing messages for social networks. We have looked deeper into Facebook as a social media and political parties on this platform. We focused on and observed their different ways of developing messages in their Facebook feed and the reactions they generated. We found tendencies saying that pictures and videos have a great effect on a engagement generated in the posts. This proves that visual communication is a crucial tool for political strategic communications within the networks of social media.

The increasing usage of social networking sites, such as Facebook has changed the way that corporations and customer interact with each other. New ways of customer-corporation interactions evolve constantly, enabling customers to participate and co-create value with the corporations. An organisation that has taken this a step further is Skånetrafiken, which uses Facebook as a channel for its customer service. This thesis focuses in the interactions that occur between Skånetrafiken and its customers, which in this case takes place on Facebook.   The purpose of this thesis is to explore the what, how and why customer and corporation interaction occur on Skånetrafiken's Facebook page. In order to approach the phenomenon of co-creation, we conducted a case study as a research design and strategy. Data collection methods we used were observations on Skånetrafiken’s Facebook page, an interview and a focus group discussion.     The findings indicate that there must be an engagement for the co-creation process to begin and that the co-creation process is continuous rather than a fixed model. It further turned out that different types of interactions occur, not only customer-to-corporation, but also customer-to-customer and customer-to-employee interactions. The limitations of the study imply that the findings cannot be generalised on all organisations since only one organisation have been examined. This thesis further gives a practical implication by presenting an applicable framework for co-creation on Facebook. Additionally, few if any have previously studied phenomenon of co-creation on Facebook, which contributes to the original value of the thesis.

The study of social network dynamics has become an increasingly important component of many disciplines in the social sciences. In the past decade, statistical models and methods have been proposed which permit researchers to draw statistical inference on these dynamics. This thesis builds on one such family of models, the stochastic actor oriented model (SAOM) proposed by Snijders [2001]. Goodness of fit for SAOMs is an area that is only just beginning to be filled in with appropriate methods. This thesis proposes a Mahalanobis distance based, Monte Carlo goodness of fit test that can depend on arbitrary features of the observed network data and covariates. As remediating poor fit can be a difficult process, a modified model distance (MMD) estimator is devised that can help researchers to choose among a set of model elaborations. In practice, panel data is typically used to draw SAOM-based inference. This thesis also proposes a score-type test for time heterogeneity between the waves in the panel that is computationally cheap and fits into a convenient, forward model selecting workflow. Next, this thesis proposes a rigorous method for aggregating so-called relational event data (e.g. emails and phone calls) by extending the SAOM family to a family of hidden Markov models that suppose a latent social network is driving the observed relational events. Finally, this thesis proposes a measurement model for SAOMs inspired by error-in-variables (EiV) models employed in an array of disciplines. Like the relational event aggregation model, the measurement model is a hidden Markov model extension to the SAOM family. These models allow the researcher to specify the form of the mesurement error and buffer against potential attenuating biases and other problems that can arise if the errors are ignored.

The structure of social networks, and people's position within these networks, are important predictors of many individual and group-level outcomes. One type of social networks that is regularly studied are the mutually interdependent relations of friends. This thesis focusses on friendship networks between adolescents in the context of schools. Arguably the most important and consistently found regularities in adolescent friendship networks are i) the tendency of friendships to be mutual, called reciprocity; ii) their tendency to cluster in groups, known as transitivity; and iii) the tendency of friendships to be present between those that are similar to one another, called homophily. Various social theories originating in different disciplines have theoretically proposed and empirically found micro-mechanisms that explain the regular occurrence of these substructures in friendship networks. This thesis introduces a framework of how the relation between these different networks tendencies can be understood. I propose that each of the three network evolution mechanisms can be connected to a type of social situation in which friends interact to form and maintain their friendships. Social situations that are dyadic and only involve two persons are connected to reciprocal friendships. Group-based social situations, on the other hand, are related to transitivity and homophily, where the groups are either defined socially or through common characteristics. Starting from this proposition, I suggest that when two adolescents share one forum for interaction with one another, i.e. they regularly meet within one of the social situations, meeting in additional other situations does not increase the likelihood of a friendship tie existing as much as could be expected from the sum of the effect of meeting in either situation. Consequently, I expect a negative interaction between the different network mechanisms. After a series of empirical analyses that support the outlined reasoning, I use the developed perspective to investigate how the micro-mechanisms contribute differentially to the creation of newly formed friendships and to the maintenance of already existing friendships. Finally, I show how a situational understanding of friendship can be used to differentiate which friendships are most important for social influence and for peer pressure.

Social network analysis (SNA) provides tools to examine relationships between people. Text mining (TM) allows capturing the text they produce in Web 2.0 applications, for example, however it neglects their social structure. This paper applies an approach to combine the two methods named "content-based SNA" (CB-SNA). Using the R mailing lists, R-help and R-devel, we show how this combination can be used to describe people's interests and to find out if authors who have similar interests actually communicate. We find that the expected positive relationship between sharing interests and communicating gets stronger as the centrality scores of authors in the communication networks increase. / Series: Research Report Series / Department of Statistics and Mathematics

Twitter generates the majority of its revenue from advertising. Third parties pay to have their products advertised on Twitter through: tweets, accounts and trends. However, spammers can use Sybil accounts (fake accounts) [21] to advertise and avoid paying for it. Sybil accounts are highly active on Twitter performing advertising campaigns to serve their clients [5]. They aggressively try to reach a large audience to maximize their influence. These accounts have similar behavior if controlled by the same master. Most of their spam tweets include a shortened URL to trick users into clicking on it. Also, since they share resources with each other, they tend to tweet similar trending topics to attract a larger audience. However, some Sybil accounts do not spam aggressively to avoid being detected [22], rendering it difficult for traditional spam detectors to be effective in detecting low spamming Sybil accounts. In this paper, I investigate additional criteria to measure the similarity between accounts on Twitter. I propose an algorithm to define the correlation among accounts by investigating their tweeting habits and content. Given known labeled accounts by spam detectors, this approach can detect hidden accounts that are closely related to labeled accounts but are not detected by traditional spam detection approaches.