Den mörka triaden (machiavellianism, psykopati och narcissism) är en modell för att beskriva, förklara och förutse socialt ogynnsamt beteende. Dessa personlighetsdrag har, enligt tidigare forskning, en påverkan på hur individer skapar och upprätthåller sociala relationer. Den föreliggande studien har undersökt sambandet mellan den mörka triaden och strukturella (antal vänner/nära vänner) såväl som funktionella (viktiga funktioner som socialt stöd medför) aspekter av socialt stöd. För att mäta personlighetsdragen i den mörka triaden samt socialt stöd användes självskattningsformulären Dark Triad Dirty Dozen (DTDD) och Social Provision Scale (SPS) samt egenformulerade frågor om antal vänner respektive nära vänner. Tvåhundraåttiofyra personer deltog i den internetbaserade studien. Resultatet visade på ett signifikant samband mellan psykopati och funktionella aspekter av socialt stöd; ju högre skattningar inom psykopati desto lägre upplevt socialt stöd. Sambandet mellan den mörka triaden och socialt stöd undersöktes vidare i regressionsanalyser, där personlighetsdragen inom mörka triaden användes som prediktorer för socialt stöd. Resultatet av dessa analyser visade att psykopati signifikant predicerade lägre upplevt socialt stöd, även när de demografiska variablerna kön, ålder, utbildningsnivå och civilstånd kontrollerades för. Inga signifikanta samband mellan varken machiavellianism eller narcissism och upplevt socialt stöd kunde påvisas. Signifikanta samband mellan den mörka triaden och den strukturella delen av socialt stöd kunde inte bekräftas. Sammanfattningsvis verkar de olika personlighetsdragen i den mörka triaden skilja sig i hur de påverkar upplevt socialt stöd. Ytterligare forskning krävs för öka kunskapen om socialt stöd inom den mörka triaden. / The dark triad (machiavellianism, psychopathy, and narcissism) is a model to describe and predict socially adverse behavior. These personality traits have been shown to affect how individuals create and maintain social relationships. The present study examined the relationship between the dark triad and structural (number of friends/close friends) as well as functional (important functions that social support entails) aspects of social support. To measure personality traits in the dark triad and social support, the Dark Triad Dirty Dozen (DTDD) and Social Provision Scale (SPS) were used, as well as purpose-made questions about number of friends and close friends. Two hundred eighty-four individuals participated in the internet-based study. The results showed a significant relationship between psychopathy and functional aspects of social support; high scores in psychopathy indicated lower social support. The relationship between the dark triad and social support was further investigated in regression analyzes, where personality traits within the dark triad were used as predictors of social support. Psychopathy predicted lower perceived social support, even when the demographic variables gender, age, level of education and civil status were controlled for. No significant association between either machiavellianism or narcissism and perceived social support could be proven. Significant correlations between the dark triad and the structural part of social support could not be confirmed. In summary, the different personality traits in the dark triad seem to differ in how they affect social support. Further research is needed to increase knowledge regarding social support within the dark triad.

This Ph.D. dissertation focuses on a comprehensive study of seismic waveform similarity aiming at two themes: (1) reliable identification of repeating earthquakes (repeaters) and (2) investigation of the detailed source process of induced seismicity through the three-dimensional spatiotemporal evolution of mainly neighbouring earthquakes. Theme 1: Reliable identification of repeaters. Repeaters, occurring repeatedly on the same fault patch with nearly identical waveforms, are usually identified with the match-filtering (MF) method which essentially measures the degree of waveform similarity between an earthquake pair through the corresponding cross-correlation coefficient (CC). However, the performance of the MF method can be severely affected by the length of the cross‐correlation window, the frequency band of the applied digital filter, and the presence of a large‐amplitude wave train. To optimize the performance of MF, I first examine the effects of different operational parameters and determine generic rules for selecting the window length and the optimal frequency passband. To minimize the impact of a large‐amplitude wave train, I then develop a new method, named the match-filtering with multisegment cross-correlation (MFMC) method. By equally incorporating the contributions from various segments of the waveforms, the new method is much more effective in capturing the minor waveform discrepancy between an event pair due to location difference and hence is more reliable in detecting potential repeaters and discriminating non-repeaters with large inter-event separation. With both synthetic and borehole array waveform data, I further reveal that waveform similarity is controlled by not only the inter-event separation but also many other factors, including station azimuth, epicentral distance, velocity structure, etc. Therefore, in contrast to the traditional view, the results indicate that waveform similarity alone is insufficient to unambiguously identify true repeaters. For reliable repeater identification, we should rely on a physics-based approach considering both the overlapped source area and magnitude difference. Specifically, I define an event pair to be true repeaters if their inter-event separation is smaller than the rupture radius of the larger event and their magnitude difference is no more than 1. For the precise estimation of inter-event distance in cases of limited data, I develop the differential traveltime double-difference (DTDD) method which relies on the relative S-P differential traveltime. The findings of this study imply that previously identified repeaters and their interpretations/hypotheses potentially can be biased and hence may need a systematic reexamination. Theme 2: Investigation of the detailed source process of induced seismicity. Earthquakes induced by hydraulic fracturing (HF), especially those with large magnitudes, are often observed to have occurred near/after well completion. The delayed triggering of induced seismicity with respect to injection commencement poses serious challenges for risk mitigation and hazard assessment. By performing waveform cross-correlation and hierarchical clustering analysis, I reveal a high-resolution three-dimensional source migration process with mainshock delayed triggering that is probably controlled by local hydrogeological conditions. The results suggest that poroelastic effects might contribute to induced seismicity but are likely insufficient to activate a non-critically stressed fault of sufficient size. My analysis shows that the rapid pore-pressure build-up from HF can be very localized and capable of producing large, felt earthquakes on non-critically stressed fault segments. I further infer that the number of critically stressed, large intraplate faults should be very limited, and that reactivation of such faults may require sufficient pore-pressure accumulation. The findings of this study may also explain why so few fluid injections are seismogenic. / Graduate