Social Media Analytics : Ein interdisziplinärer Ansatz und seine Implikationen für die Wirtschaftsinformatik [Social Media Analytics - An Interdisciplinary Approach and Its Implications for Information Systems]

Social Media Analytics ist ein neuer Forschungsbereich, in dem interdisziplinäre Methoden kombiniert, erweitert und angepasst werden, um Social-Media-Daten auszuwerten. Neben der Beantwortung von Forschungsfragen ist es ebenfalls ein Ziel, Architekturentwürfe für die Entwicklung neuer Informationssysteme und Anwendungen bereitzustellen, die auf sozialen Medien basieren. Der Beitrag stellt die wichtigsten Aspekte des Bereichs Social Media Analytics vor und verweist auf die Notwendigkeit einer fächerübergreifenden Forschungsagenda, für deren Erstellung und Bearbeitung der Wirtschaftsinformatik eine wichtige Rolle zukommt.

Twitter-archive und die Herausforderungen von "Big Social Data" für die Medien- und Kommunikationswissenschaft

Twitter ist eine besonders nützliche Quelle für Social-Media-Daten: mit dem Twitter-API (dem Application Programming Interface, das einen strukturierten Zugang zu Kommunikationsdaten in standardisierten Formaten bietet) ist es Forschern möglich, mit ein wenig Mühe und ausreichenden technische Ressourcen sehr große Archive öffentlich verbreiteter Tweets zu bestimmten Themen, Interessenbereichen, oder Veranstaltungen aufzubauen. Grundsätzlich liefert das API sehr langen Listen von Hunderten, Tausenden oder Millionen von Tweets und den Metadaten zu diesen Tweets; diese Daten können dann auf verschiedentlichste Weise extrahiert, kombiniert, und visualisiert werden, um die Dynamik der Social-Media-Kommunikation zu verstehen. Diese Forschung ist häufig um althergebrachte Fragestellungen herum aufgebaut, wird aber in der Regel in einem bislang unbekannt großen Maßstab durchgeführt. Die Projekte von Medien- und Kommunikationswissenschaftlern wie Papacharissi und de Fatima Oliveira (2012), Wood und Baughman (2012) oder Lotan et al. (2011) – um nur eine Handvoll der letzten Beispiele zu nennen – sind grundlegend auf Twitterdatensätze aufgebaut, die jetzt routinemäßig Millionen von Tweets und zugehörigen Metadaten umfassen, erfaßt nach einer Vielzahl von Kriterien. Was allen diesen Fällen gemein ist, ist jedoch die Notwendigkeit, neue methodische Wege in der Verarbeitung und Analyse derart großer Datensätze zur medienvermittelten sozialen Interaktion zu gehen.

Occupational and non-occupational risk factors in bladder cancer patients in an industrialized area located in former East-Germany [Berufliche und außerberufliche Risikofaktoren für das Harnblasenkarzinom in einem ehemaligen Industriegebiet der neuen Bundesländer]

Purpose: Several occupational carcinogens are metabolized by polymorphic enzymes. The distribution of the polymorphic enzymes N-acetyltransferase 2 (NAT2; substrates: aromatic amines), glutathione S-transferase M1 (GSTM1; substrates: e.g., reactive metabolites of polycyclic aromatic hydrocarbons), and glutathione S-transferase T1 (GSTT1; substrates: small molecules with 1-2 carbon atoms) were investigated. Material and Methods: At the urological department in Lutherstadt Wittenberg, 136 patients with a histologically proven transitional cell cancer of the urinary bladder were investigated for all occupations performed for more than 6 months. Several occupational and non-occupational risk factors were asked. The genotypes of NAT2, GSTM1, and GSTT1 were determined from leucocyte DNA by PCR. Results: Compared to the general population in Middle Europe, the percentage of GSTT1 negative persons (22.1 %) was ordinary; the percentage of slow acetylators (59.6%) was in the upper normal range, while the percentage of GSTM1 negative persons (58.8%) was elevated in the entire group. Shifts in the distribution of the genotypes were observed in subgroups who had been exposed to asbestos (6/6 GSTM1 negative, 5/6 slow acetylators), rubber manufacturing (8/10 GSTM1 negative), and chlorinated solvents (9/15 GSTM1 negative). Conclusions: The overrepresentation of GSTM1 negative bladder cancer patients also in this industrialized area and more pronounced in several occupationally exposed subgroups points to an impact of the GSTM1 negative genotype in bladder carcinogenesis. [Article in German]

Was wollen jüngere und ältere Erwerbstätige erreichen? Altersbezogene Unterschiede in den Inhalten und Merkmalen beruflicher Ziele [What do younger and older workers want to accomplish? Age-related differences in content and characteristics of occupational goals ]

Demographic changes necessitate that companies commit younger workers and motivate older workers through work design. Age-related differences in occupational goals should be taken into account when accomplishing these challenges. In this study, we investigated goal contents and goal characteristics of employees from different age groups. We surveyed 150 employees working in the service sector (average age = 44 years, age range 19 to 60 years) on their most important occupational goals. Employees who stated goals from the area of organizational citizenship were significantly older than employees with other goals. Employees who stated goals from the areas of training and pay/career were significantly younger than employees with other goals. After controlling for gender, education, and work characteristics, no age-related differences were found in the goal areas teamwork, job security, working time, well-being, and new challenges. In addition, no relationships were found between age and the goal characteristics specificity, planning intensity, as well as positive and negative goal emotions. We recommend that companies provide older workers with more opportunities for organizational citizenship and commit younger workers by providing development opportunities and adequate pay

Lernen im Team: Zusammenhänge zwischen Personen- und Teammerkmalen und der Leistung von Multiplikatoren [Learning in teams: Relationships between individual and team characteristics and the performance of multipliers]

The continuous mutual transfer of knowledge and skills within work teams is increasingly important for organizational practice. According to the situational and experience-based approaches of applied learning research, certain individual and social prerequisites have to be met for successful learning in teams. In a field study at an automobile production site, it was investigated which personal characteristics of multipliers and which characteristics of teams are related to the performance of multipliers in 31 teams with 291 coworkers. Using multi-level analyses (HLM), the amount of variance explained by the predictor variables in teaching success of multipliers and learning success of coworkers was examined. Results showed that multipliers' conscientiousness and team cohesion were related to teaching success of multipliers; extraversion and team cohesion were related to the learning success of coworkers. In closing, the scientific and practical implications for the investigation and promotion of work-based learning processes in teams are discussed.