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Institute
- Extern (12)
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With the surging reliance on videoconferencing tools, users may find themselves staring at their reflections for hours a day. We refer to this phenomenon as self-referential information (SRI) consumption and examine its consequences and the mechanism behind them. Building on self-awareness research and the strength model of self-control, we argue that SRI consumption heightens the state of self-awareness and thereby depletes participants’ mental resources, eventually undermining virtual meeting (VM) outcomes. Our findings from a European employee sample revealed contrary effects of SRI consumption across speaker vs listener roles. Engagement with self-view is positively associated with self-awareness, which, in turn, is negatively related to satisfaction with VM process, perceived productivity, and enjoyment. Looking at the self while listening to others exhibits adverse direct and indirect (via self-awareness) effects on VM outcomes. However, looking at the self when speaking exhibits positive direct effects on satisfaction with VM process and enjoyment.
It is a well-attested finding in head-initial languages that individuals with aphasia (IWA) have greater difficulties in comprehending object-extracted relative clauses (ORCs) as compared to subject-extracted relative clauses (SRCs). Adopting the linguistically based approach of Relativized Minimality (RM; Rizzi, 1990, 2004), the subject-object asymmetry is attributed to the occurrence of a Minimality effect in ORCs due to reduced processing capacities in IWA (Garraffa & Grillo, 2008; Grillo, 2008, 2009). For ORCs, it is claimed that the embedded subject intervenes in the syntactic dependency between the moved object and its trace, resulting in greater processing demands. In contrast, no such intervener is present in SRCs. Based on the theoretical framework of RM and findings from language acquisition (Belletti et al., 2012; Friedmann et al., 2009), it is assumed that Minimality effects are alleviated when the moved object and the intervening subject differ in terms of relevant syntactic features. For German, the language under investigation, the RM approach predicts that number (i.e., singular vs. plural) and the lexical restriction [+NP] feature (i.e., lexically restricted determiner phrases vs. lexically unrestricted pronouns) are considered relevant in the computation of Minimality. Greater degrees of featural distinctiveness are predicted to result in more facilitated processing of ORCs, because IWA can more easily distinguish between the moved object and the intervener.
This cumulative dissertation aims to provide empirical evidence on the validity of the RM approach in accounting for comprehension patterns during relative clause (RC) processing in German-speaking IWA. For that purpose, I conducted two studies including visual-world eye-tracking experiments embedded within an auditory referent-identification task to study the offline and online processing of German RCs. More specifically, target sentences were created to evaluate (a) whether IWA demonstrate a subject-object asymmetry, (b) whether dissimilarity in the number and/or the [+NP] features facilitates ORC processing, and (c) whether sentence processing in IWA benefits from greater degrees of featural distinctiveness. Furthermore, by comparing RCs disambiguated through case marking (at the relative pronoun or the following noun phrase) and number marking (inflection of the sentence-final verb), it was possible to consider the role of the relative position of the disambiguation point. The RM approach predicts that dissimilarity in case should not affect the occurrence of Minimality effects. However, the case cue to sentence interpretation appears earlier within RCs than the number cue, which may result in lower processing costs in case-disambiguated RCs compared to number-disambiguated RCs.
In study I, target sentences varied with respect to word order (SRC vs. ORC) and dissimilarity in the [+NP] feature (lexically restricted determiner phrase vs. pronouns as embedded element). Moreover, by comparing the impact of these manipulations in case- and number-disambiguated RCs, the effect of dissimilarity in the number feature was explored. IWA demonstrated a subject-object asymmetry, indicating the occurrence of a Minimality effect in ORCs. However, dissimilarity neither in the number feature nor in the [+NP] feature alone facilitated ORC processing. Instead, only ORCs involving distinct specifications of both the number and the [+NP] features were well comprehended by IWA. In study II, only temporarily ambiguous ORCs disambiguated through case or number marking were investigated, while controlling for varying points of disambiguation. There was a slight processing advantage of case marking as cue to sentence interpretation as compared to number marking.
Taken together, these findings suggest that the RM approach can only partially capture empirical data from German IWA. In processing complex syntactic structures, IWA are susceptible to the occurrence of the intervening subject in ORCs. The new findings reported in the thesis show that structural dissimilarity can modulate sentence comprehension in aphasia. Interestingly, IWA can override Minimality effects in ORCs and derive correct sentence meaning if the featural specifications of the constituents are maximally different, because they can more easily distinguish the moved object and the intervening subject given their reduced processing capacities. This dissertation presents new scientific knowledge that highlights how the syntactic theory of RM helps to uncover selective effects of morpho-syntactic features on sentence comprehension in aphasia, emphasizing the close link between assumptions from theoretical syntax and empirical research.
Relativistic pair beams produced in the cosmic voids by TeV gamma rays from blazars are expected to produce a detectable GeV-scale cascade emission missing in the observations. The suppression of this secondary cascade implies either the deflection of the pair beam by intergalactic magnetic fields (IGMFs) or an energy loss of the beam due to the electrostatic beam-plasma instability. IGMF of femto-Gauss strength is sufficient to significantly deflect the pair beams reducing the flux of secondary cascade below the observational limits. A similar flux reduction may result in the absence of the IGMF from the beam energy loss by the instability before the inverse Compton cooling. This dissertation consists of two studies about the instability role in the evolution of blazar-induced beams.
Firstly, we investigated the effect of sub-fG level IGMF on the beam energy loss by the instability. Considering IGMF with correlation lengths smaller than a few kpc, we found that such fields increase the transverse momentum of the pair beam particles, dramatically reducing the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. Our results show that the IGMF eliminates beam plasma instability as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission and hence can be excluded.
Secondly, we probed how the beam-plasma instability feeds back on the beam, using a realistic two-dimensional beam distribution. We found that the instability broadens the beam opening angles significantly without any significant energy loss, thus confirming a recent feedback study on a simplified one-dimensional beam distribution. However, narrowing diffusion feedback of the beam particles with Lorentz factors less than 1e6 might become relevant even though initially it is negligible. Finally, when considering the continuous creation of TeV pairs, we found that the beam distribution and the wave spectrum reach a new quasi-steady state, in which the scattering of beam particles persists and the beam opening angle may increase by a factor of hundreds. This new intrinsic scattering of the cascade can result in time delays of around ten years, thus potentially mimicking the IGMF deflection. Understanding the implications on the GeV cascade emission requires accounting for inverse Compton cooling and simulating the beam-plasma system at different points in the IGM.
Das Rechtslexikon
(2024)
Kompetenz im handlichen Format in über 1.400 Stichwörtern, 26 Tabellen und Schaubildern zu allen wichtigen Rechtsgebieten: Zivilrecht (z. B. Familien- und Erbrecht, Versicherungsrecht), Arbeitsrecht, Öffentliches Recht (z. B. Baurecht, Staats- und Verfassungsrecht, Umweltrecht, Verwaltungsrecht), Sozialrecht (z. B. Arbeitslosen- und Rentenversicherung), Strafrecht (einschließlich Jugendstrafrecht und Ordnungswidrigkeiten) sowie ihren europa- und völkerrechtlichen Bezügen.
Das Rechtslexikon ist in seiner 2. Auflage ergänzt worden um zahlreiche neue und aktuelle Begriffe wie Impfpflicht, Quarantäne, Radwegbenutzung, Schutzpflicht, Crowdworking, Homeoffice/mobiles Arbeiten, Datenschutzgrundverordnung, Mediation, Smart Contract u.v.a.m. Das Lexikon erklärt außerdem Normen und Grundsätze des deutschen und europäischen Rechts, knapp, zuverlässig und verständlich. Grundlegende Fragen und Zusammenhänge werden in besonderen Überblicksartikeln erläutert. Querverweise machen auf verwandte Themen im Lexikon aufmerksam.
Ein Lexikon für juristisch interessierte Laien, Studierende sowie Schülerinnen und Schüler.
Classification, prediction and evaluation of graph neural networks on online social media platforms
(2024)
The vast amount of data generated on social media platforms have made them a valuable source of information for businesses, governments and researchers. Social media data can provide insights into user behavior, preferences, and opinions. In this work, we address two important challenges in social media analytics. Predicting user engagement with online content has become a critical task for content creators to increase user engagement and reach larger audiences. Traditional user engagement prediction approaches rely solely on features derived from the user and content. However, a new class of deep learning methods based on graphs captures not only the content features but also the graph structure of social media networks.
This thesis proposes a novel Graph Neural Network (GNN) approach to predict user interaction with tweets. The proposed approach combines the features of users, tweets and their engagement graphs. The tweet text features are extracted using pre-trained embeddings from language models, and a GNN layer is used to embed the user in a vector space. The GNN model then combines the features and graph structure to predict user engagement. The proposed approach achieves an accuracy value of 94.22% in classifying user interactions, including likes, retweets, replies, and quotes.
Another major challenge in social media analysis is detecting and classifying social bot accounts. Social bots are automated accounts used to manipulate public opinion by spreading misinformation or generating fake interactions. Detecting social bots is critical to prevent their negative impact on public opinion and trust in social media. In this thesis, we classify social bots on Twitter by applying Graph Neural Networks. The proposed approach uses a combination of both the features of a node and an aggregation of the features of a node’s neighborhood to classify social bot accounts. Our final results indicate a 6% improvement in the area under the curve score in the final predictions through the utilization of GNN.
Overall, our work highlights the importance of social media data and the potential of new methods such as GNNs to predict user engagement and detect social bots. These methods have important implications for improving the quality and reliability of information on social media platforms and mitigating the negative impact of social bots on public opinion and discourse.
The present paper proposes a novel approach for equilibrium selection in the infinitely repeated prisoner’s dilemma where players can communicate before choosing their strategies. This approach yields a critical discount factor that makes different predictions for cooperation than the usually considered sub-game perfect or risk dominance critical discount factors. In laboratory experiments, we find that our factor is useful for predicting cooperation. For payoff changes where the usually considered factors and our factor make different predictions, the observed cooperation is consistent with the predictions based on our factor.
The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data.
The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient.
The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.
I need to move it, move It!
(2024)
Purpose
Student interest and learning success is an important component of teaching learning research. However, while the impact of emotions and psychological needs on students' achievements has been a focus of research, the impact of their physiological needs has been under studied. In this explorative study, I examine what impact the physiological and psychological needs of student teachers have on their feelings, motivation, and interest in different learning settings.
Approach
The research method used was the daily reconstruction method and included the Felix-App, a new digital research and feedback tool that allows the measurement of feelings, needs, motivation, and interest in real time.
Findings
The results suggest the importance of physiological needs for perceived emotions, motivation, and interest in the learning subject. The psychological needs, on the other hand, are of less importance.
Originality
The Felix-App is an innovative tool to learn more about learners' emotions and needs in real learning settings. The importance of physiological needs has been known since Maslow, but should be considered much more in the context of teaching and learning research in the future. There is a need for further research on the importance of physical aspects in learning.
Lust auf Verzicht
(2024)
Der globale Klimawandel nimmt weiter bedrohlich zu. Hitzewellen, Flutkatastrophen und Waldbrände gehören fast schon zum Alltag. Trotzdem ist die Bereitschaft in der deutschen Bevölkerung gering, selbst einen Beitrag zum Klimaschutz zu leisten. Das überrascht, denn in Umfragen bekennt sich immer eine große Mehrheit zum Klimaschutz. Allerdings haben wohl viele einen Klimaschutz im Kopf, der persönlich nichts kosten und nichts verändern darf.
Ingo Balderjahn setzt sich mit diesem Widerspruch aus verhaltenswissenschaftlicher Sicht auseinander und legt offen, warum viele weiterhin ungebremst verschwenderisch und klimaschädlich konsumieren. Andererseits gibt es durchaus Menschen, die deutlich weniger konsumieren, als sie sich finanziell leisten könnten. Diese Minderheit in Deutschland verzichtet freiwillig auf eher unnötige und kurzlebige Güter - ohne irgendetwas dabei zu entbehren. Im Gegenteil: Genügsame Konsumgewohnheiten stärken die persönliche Selbstbestimmung, Unabhängigkeit und Zufriedenheit.
Ausgehend von der Beobachtung, dass die aktuelle Digitalisierungsforschung die Ambivalenz der Digitalisierung zwar erkennt, aber nicht zum Gegenstand ihrer Analysen macht, fokussiert die vorliegende kumulative Dissertation auf die ambivalente Dichotomie aus Potenzialen und Problemen, die mit digitalen Transformationen von Organisationen einhergeht. Entlang von sechs Publikationen wird mit einem systemtheoretischen Blick auf Organisationen die spannungsvolle Dichotomie hinsichtlich dreier ambivalenter Verhältnisse aufgezeigt: Erstens wird in Bezug auf das Verhältnis von Digitalisierung und Postbürokratie deutlich, dass digitale Transformationen das Potenzial aufweisen, postbürokratische Arbeitsweisen zu erleichtern. Parallel ergibt sich das Problem, dass auf Konsens basierende postbürokratische Strukturen Digitalisierungsinitiativen erschweren, da diese auf eine Vielzahl von Entscheidungen angewiesen sind. Zweitens zeigt sich mit Blick auf das ambivalente Verhältnis von Digitalisierung und Vernetzung, dass einerseits organisationsweite Kooperation ermöglicht wird, während sich andererseits die Gefahr digitaler Widerspruchskommunikation auftut. Beim dritten Verhältnis zwischen Digitalisierung und Gender deutet sich das mit neuen digitalen Technologien einhergehende Potenzial für Gender Inklusion an, während zugleich das Problem einprogrammierter Gender Biases auftritt, die Diskriminierungen oftmals verschärfen. Durch die Gegenüberstellung der Potenziale und Probleme wird nicht nur die Ambivalenz organisationaler Digitalisierung analysierbar und verständlich, es stellt sich auch heraus, dass mit digitalen Transformationen einen doppelte Formalisierung einhergeht: Organisationen werden nicht nur mit den für Reformen üblichen Anpassungen der formalen Strukturen konfrontiert, sondern müssen zusätzlich formale Entscheidungen zu Technikeinführung und -beibehaltung treffen sowie formale Lösungen etablieren, um auf unvorhergesehene Potenziale und Probleme reagieren. Das Ziel der Dissertation ist es, eine analytisch generalisierte Heuristik an die Hand zu geben, mit deren Hilfe die Errungenschaften und Chancen digitaler Transformationen identifiziert werden können, während sich parallel ihr Verhältnis zu den gleichzeitig entstehenden Herausforderungen und Folgeproblemen erklären lässt.