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Der Forschungsbericht bietet die Auswertung studentischer Seminarportfolios der Lehrveranstaltung „Biblische Theologie“ im Studiengang Religionspädagogik und Soziale Arbeit an der Hochschule Hannover. Diese Portfolioanalyse ist eine Teilstudie aus dem Gesamtprojekt „Untersuchung bibelhermeneutischer Prozesse im Rahmen angewandter Wissenschaften“, das von 2016-2021 mit zwei Kohorten des Studiengangs von einem interdisziplinären Forschungsteam an der Fakultät V der Hochschule Hannover durchgeführt wurde. Das Forschungsinteresse zielt darauf, Veränderungen des Grundverständnisses der Bibel bei Studierenden der Religionspädagogik und der Sozialen Arbeit zu beschreiben. Arbeitsergebnisse aus 32 Portfolios werden mit Hilfe der qualitativen Inhaltsanalyse ausgewertet. Im Ergebnis können bei den meisten Studierenden Veränderungen des intuitiven Grundverständnisses beschrieben und kategorisiert werden. Bibelhermeneutische Prozesse im Studium verlaufen einerseits individuell, andererseits werden auch Entwicklungstendenzen in der untersuchten Gruppe erkennbar. Das Gesamtergebnis wird in ein Theoriekonzept bibelhermeneutischer Kompetenz eingeordnet. Daneben werden weitere fachliche und persönliche Kompetenzentwicklungen der Studierenden dargestellt.
Für Fachangestellte für Medien- und Informationsdienste (FaMIs) ist berufsbegleitendes Studieren eine erfolgreiche Maßnahme zur Höherqualifizierung. Bibliotheken können ihrerseits im Rahmen der Personalentwicklung mit der Unterstützung von studierenden Mitarbeitenden dem Fachkräftemangel entgegenwirken. Der Beitrag stellt die Personalentwicklungsmaßnahme am Beispiel des Bachelor-Studiengangs „Informationsmanagement – berufsbegleitend“ der Hochschule Hannover vor. Es werden Informationen aus der Beratungspraxis dargelegt und die mögliche Unterstützung durch die entsendenden Bibliotheken aufgezeigt.
Data and Information Science: Book of Abstracts at BOBCATSSS 2022 Hybrid Conference, 23rd - 25th of May 2022, Debrecen.
This year marks the 30th anniversary of the BOBCATSSS. The BOBCATSSS is an international, annual symposium designed for librarians and information professionals in a rapidly changing environment. Over the past 30 years, the conference has included exciting topics, great venues, interested guests and engaging presenters.
This year we would like to introduce the topics of the many papers presented in the Book of Abstracts for the first time in presence at the University of Debrecen and hybrid. The Book of Abstracts provides an overview of all presentations given at BOBCATSSS. Presentations are listed in alphabetical order by title and include speeches, Pecha Kuchas, posters and workshops.
The theme of BOBCATSSS is Data and Information Science. Data and information are the basis for decisions and processes in business, politics and science. Particularly important in the current era of digital transformation. This is exactly where this year's subthemes come in. They deal with data science, openness as well as institutional roles.
This paper proposes an extended Petri net formalism as a suitable language for composing optimal scheduling problems of industrial production processes with real and binary decision variables. The proposed approach is modular and scalable, as the overall process dynamics and constraints can be collected by parsing of all atomic elements of the net graph. To conclude, we demonstrate the use of this framework for modeling the moulding sand preparation process of a real foundry plant.
A semiparametric approach for meta-analysis of diagnostic accuracy studies with multiple cut-offs
(2022)
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without targetcondition). If the outcome of a diagnostic test is binary, results from different studies can easily be summarized in a meta-analysis. However, if the diagnostic test is based on a discrete or continuous measure (e.g., a biomarker), several cut-offs within one study as well as among different studies are published. Instead of taking all information of the cut-offs into account in the meta-analysis, a single cut-off per study is often selected arbitrarily for the analysis, even though there are statistical methods for the incorporation of several cut-offs. For these methods, distributional assumptions have to be met and/or the models may not converge when specific data structures occur. We propose a semiparametric approach to overcome both problems. Our simulation study shows that the diagnostic accuracy is underestimated, although this underestimation in sensitivity and specificity is relatively small. The comparative approach of Steinhauser et al. is better in terms of coverage probability, but may lead to convergence problems. In addition to the simulation results, we illustrate the application of the semiparametric approach using a published meta-analysis for a diagnostic test differentiating between bacterial and viral meningitis in children.
Dramatic increases in the number of cyber security attacks and breaches toward businesses and organizations have been experienced in recent years. The negative impacts of these breaches not only cause the stealing and compromising of sensitive information, malfunctioning of network devices, disruption of everyday operations, financial damage to the attacked business or organization itself, but also may navigate to peer businesses/organizations in the same industry. Therefore, prevention and early detection of these attacks play a significant role in the continuity of operations in IT-dependent organizations. At the same time detection of various types of attacks has become extremely difficult as attacks get more sophisticated, distributed and enabled by Artificial Intelligence (AI). Detection and handling of these attacks require sophisticated intrusion detection systems which run on powerful hardware and are administered by highly experienced security staff. Yet, these resources are costly to employ, especially for small and medium-sized enterprises (SMEs). To address these issues, we developed an architecture -within the GLACIER project- that can be realized as an in-house operated Security Information Event Management (SIEM) system for SMEs. It is affordable for SMEs as it is solely based on free and open-source components and thus does not require any licensing fees. Moreover, it is a Self-Contained System (SCS) and does not require too much management effort. It requires short configuration and learning phases after which it can be self-contained as long as the monitored infrastructure is stable (apart from a reaction to the generated alerts which may be outsourced to a service provider in SMEs, if necessary). Another main benefit of this system is to supply data to advanced detection algorithms, such as multidimensional analysis algorithms, in addition to traditional SIEMspecific tasks like data collection, normalization, enrichment, and storage. It supports the application of novel methods to detect security-related anomalies. The most distinct feature of this system that differentiates it from similar solutions in the market is its user feedback capability. Detected anomalies are displayed in a Graphical User Interface (GUI) to the security staff who are allowed to give feedback for anomalies. Subsequently, this feedback is utilized to fine-tune the anomaly detection algorithm. In addition, this GUI also provides access to network actors for quick incident responses. The system in general is suitable for both Information Technology (IT) and Operational Technology (OT) environments, while the detection algorithm must be specifically trained for each of these environments individually.
Die Covid-19 Pandemie hat zu einem signifikanten Anstieg der Remote Work geführt. Die Veränderung in der Interaktion und Kollaboration ist für viele agile Teams eine Herausforderung gewesen. Diverse Studien zeigen unterschiedliche Effekte und Auswirkungen auf die Zusammenarbeit agiler Teams während der Pandemie. So ist die Kommunikation sachlicher und zielgerichteter geworden. Ebenso wird eine Verminderung des sozialen Austauschs in den Teams berichtet. Unser Artikel thematisiert die Veränderung der Interaktion in agilen Teams durch die Remote Work. Wir haben eine qualitative Fallstudie bei einem agilen Software-Entwicklungsteam bei Otto durchgeführt. Unsere Ergebnisse zeigen einen Zusammenhang zwischen den Auswirkungen auf die Interaktion und der persönlichen Autonomie der Team-Mitglieder. Darüber hinaus haben wir keine signifikanten negativen Effekte durch die veränderte Interaktion auf die agile Arbeitsweise festgestellt.
Das Konzept der Agilität stiftet insbesondere im Kontext der Softwareentwicklung einen Nutzen. Es stellt sich die Frage, wie auch die öffentliche Verwaltung agiler werden und schlussendlich davon profitieren kann. Bislang liefern nur wenige Schriften eine dedizierte Auseinandersetzung mit dem Thema der agilen Verwaltung. In dieser Arbeit wird untersucht, ob agile Softwareentwicklung Ausgangspunkt einer potenziell agilen Verwaltung in Deutschland sein kann. Im Rahmen einer theorievergleichenden Gegenüberstellung wird ein Zielbild einer agilen Verwaltung ausgehend von den Merkmalen agiler Softwareentwicklung hergeleitet. Anschließend werden mögliche Spannungslinien zwischen dem entwickelten Zielbild und dem von Max Weber beschriebenen Idealtypus einer bürokratischen Verwaltung aufgedeckt. Im Ergebnis kennzeichnet eine agile Verwaltung ein Konglomerat unterschiedlicher Merkmale, die den Dimensionen Strategie, Struktur, Prozesse, Führung, Personal und Kultur zugeordnet werden können. Die öffentliche Verwaltung wird das Konzept der Agilität nicht vollständig, im Sinne der Ausprägung aller herausgearbeiteten Merkmale, organisational etablieren können. Die wesentlichen Spannungslinien ergeben sich aus den Bürokratiemerkmalen Amtshierarchie und Regelgebundenheit. Der Idealtypus einer agilen Verwaltung kann nur insofern eine Alternative zum Idealtypus der bürokratischen Verwaltung sein, als dass diejenigen Merkmale der Bürokratie, die sich mit den wesentlichen Strukturprinzipien des deutschen Staates decken, unberührt bleiben.
Ziel der nachfolgenden Arbeit ist die Erhebung des aktuellen Stands der Digitalisierung in der Landwirtschaft. Es gilt herauszufinden, wie weit landwirtschaftliche Betriebe in Deutschland heute bereits digitalisiert sind. Parallel dazu soll erörtert werden, welche Gründe eine weitergehende Digitalisierung gegenwärtig verhindern. Dabei ist zu berücksichtigen, welche Bedeutung Digitalisierung in der Landwirtschaft hat. Zur Beantwortung der Forschungsfrage werden sowohl qualitative (Systematische Literaturanalyse) als auch quantitative Forschungsmethoden (Online-Umfrage mit anschließender statistischer Auswertung) angewendet. Wesentliche Erkenntnisse dieser Arbeit sind, dass die Messung von Digitalisierungsgraden landwirtschaftlicher Betriebe mittels eines Reifegradmodells signifikante Unterschiede in der deutschen Landwirtschaft widerspiegeln und dass der Kostenfaktor einen erheblichen Druck auf den digitalen Wandel im Agrarsektor ausübt. Generationenwechsel, sowie herstellerübergreifende Lösungen stellen neben der Forderung von mehr Unterstützung seitens der Politik und öffentlicher Institutionen Diskussionspunkte dieser Abschlussarbeit dar.
Barrierefreiheit spielt eine wichtige Rolle für die Inklusion und Teilhabe von Menschen mit Behinderungen an der Gesellschaft. Mit dem Beschluss des Barrierefreiheitsstärkungsgesetzes soll ihnen ein gleichberechtigter Zugang zu bestimmten digitalen Diensten ermöglicht werden. Diese Arbeit befasst sich speziell mit den Anforderungen an die Barrierefreiheit in mobilen Anwendungen. Auf Grundlage der Web Content Accessibility Guidelines wird in dieser theoretischen Arbeit erläutert, wie eine App konzipiert und gestaltet werden muss, um barrierefrei zu sein. Das Ziel ist darzulegen, wie die verschiedenen Barrieren, die die Zugänglichkeit und Nutzbarkeit von mobilen Anwendungen für Menschen mit unterschiedlichen Arten von Behinderungen einschränken, vermieden oder beseitigt werden können. Dafür wird anhand konkreter Beispiele aufgezeigt, welche Barrieren im Zusammenhang mit verschiedenen Behinderungen die größten Schwierigkeiten bei der Bedienung auslösen. Aus der Betrachtung der international anerkannten Zugänglichkeitsrichtlinien geht hervor, dass zur Behebung dieser Probleme die Wahrnehmbarkeit, Bedienbarkeit, Verständlichkeit und Robustheit gewährleistet sein müssen, welche auch in Apps die Grundlage für Barrierefreiheit darstellen. Auf Basis dieser vier Prinzipien werden die Besonderheiten von Barrierefreiheit in mobilen Anwendungen und ihre typischen Probleme beschrieben, woraufhin Maßnahmen und Lösungen für mehr Accessibility in Apps herausgearbeitet werden. Zudem wird erläutert, ob und wie Kontrollen durchgeführt werden können, damit in Zukunft die Barrierefreiheit garantiert werden kann.
Rich literature abounds concerning the clinical effectiveness of programs aiming to produce weight gain/obesity prevention outcomes. However, there is very little evidence on how these outcomes are produced, and what interplay of factors made those programs effective (or not) in the environment that produced those effects. This study aims to describe the application of realistic evaluation in the field of obesity prevention, as an approach to unravel those components that influence the capacity of a program to produce its effects and to examine its significance in an effort to understand those components. The concepts of critical realism have informed the development of an interview topic guide, while three European programs were selected as case studies after a rigorous selection process. In total, 26 in-depth semi-structured interviews were taken, paired with personal observation and secondary data research. Several grounded context-mechanisms-outcomes (CMO) configurations were described within the respective context of each location, with the mechanisms introduced from each project resulting in distinctive outcomes. This study highlights the potential of realistic evaluation as a comprehensive framework to explain in which contextual circumstances of each program’s effects are produced, how certain underlying mechanisms produce those effects, and how to explicitly connect the context and the acting mechanisms into distinct outcome patterns, which will ultimately form unique configuration sets for each of the analyzed projects.
Complex Event Processing (CEP) is a modern software technology for the dynamic analysis of continuous data streams. CEP is able of searching extremely large data streams in real time for the presence of event patterns. So far, specifying event patterns of CEP rules is still a manual task based on the expertise of domain experts. This paper presents a novel batinspired swarm algorithm for automatically mining CEP rule patterns that express the relevant causal and temporal relations hidden in data streams. The basic suitability and performance of the approach is proven by extensive evaluation with both synthetically generated data and real data from the traffic domain.
In dieser Studie wurden Unternehmen, die Produktionsanlagen betreiben oder betreuen, zu ihrem Sicherheitsaufwand bei der Abfrage von Security Advisories für Automatisierungskomponenten befragt. Die befragten Unternehmen (vorwiegend KMU) machten Angaben zum zeitlichen, technischen und personellen Aufwand für die Auswertung von Security Advisories im Produktionsumfeld. Es wurde festgestellt, dass in vielen Unternehmen Defizite in Bezug auf diese Fragestellung bestehen. Dieses resultiert im Wesentlichen aus Mangel an Zeit und Mangel an qualifiziertem Personal. Eine in der Studie vorgeschlagene automatisierte Abfrage von Asset Inventories und eine automatisierte Zuordnung von Security Advisories zu den Assets wird von den befragten Unternehmen durchgehend als sinnvoll erachtet.
Catholic Ownership, Physician Leadership and Operational Strategies: Evidence from German Hospitals
(2022)
Previous research has revealed that Catholic hospitals are more likely follow a strategy of horizontal diversification and maximization of the number of patients treated, whereas Protestant hospitals follow a strategy of horizontal specialization and focus on vertical differentiation. However, there is no empirical evidence pertaining to this mechanism. We conduct an empirical study in a German setting and argue that physician leadership mediates the relationship between ownership and operational strategies. The study includes the construction of a model combining data from a survey and publicly available information derived from the annual quality reports of German hospitals. Our results show that Catholic hospitals opt for leadership structures that ensure operational strategies in line with their general values, i.e., operational strategies of maximizing volume throughout the overall hospital. They prefer part-time positions for chief medical officers, as chief medical officers are identified to foster strategies of maximizing the overall number of patients treated. Hospital owners should be aware that the implementation of part-time and full-time leadership roles can help to support their strategies. Thus, our results provide insights into the relationship between leadership structures at the top of an organization, on the one hand, and strategic choices, on the other.
Background and Objectives:
Drawing causal conclusions from real-world data (RWD) poses methodological challenges and risk of bias. We aimed to systematically assess the type and impact of potential biases that may occur when analyzing RWD using the case of progressive ovarian cancer.
Methods:
We retrospectively compared overall survival with and without second-line chemotherapy (LOT2) using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal structural Cox model with replicates emulating a reference randomized controlled trial (RCT). To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the
HR of the reference trial.
Results:
The reference trial showed an HR for second line vs. delayed therapy of 1.01 (95% confidence interval [95% CI]: 0.82e1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95% CI: 1.22e1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded an HR of 1.12 (95% CI: 0.96e1.28).
Conclusion:
Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.
To optimise udder health at the herd level, identifying incurable mastitis cases as well as providing an adequate therapy and culling strategy are necessary. Cows with clinical mastitis should be administered antibiotic medication if it is most likely to improve mammary cure. The somatic cell count (SCC) in milk of the monthly implemented Dairy Herd Improvement (DHI) test represents the most important tool to decide whether a cow has a promising mammary cure rate. Differential cell count (DCC) facilitates the specification of the immunological ability of defence, for example by characterising leukocyte subpopulations or cell viability. The aim of this study was to assess the DCC and cell viability in DHI milk samples regarding the cytological (CC) and bacteriological cure (BC) of the udder within a longitudinal study, thereby gaining a predictive evaluation of whether a clinical mastitis benefits from an antibiotic treatment or not. The cows enrolled in this study had an SCC above 200,000 cells/mL in the previous DHI test. Study 1 assessed the CC by reference to the SCC of two consecutive DHI tests and included 1010 milk samples: 28.4% of the mammary glands were classified as cytologically cured and 71.6% as uncured. The final mixed logistic regression model identified the total number of non-vital cells as a significant factor associated with CC. An increasing amount of non-vital cells was related to a lower individual ability for CC. Cows which were in the first or second lactation possessed a higher probability of CC than cows having a lactation number above two. If animals developed a clinical mastitis after flow cytometric investigation, the BC was examined in study 2 by analysing quarter foremilk samples microbiologically. Taking 48 milk samples, 81.3% of the mammary glands were classified as bacteriologically cured and 18.7% as uncured. The percentage of total non-vital cells tended to be lower for cows which were cured, but no significance could be observed. This study revealed that the investigation of the proportion of non-vital cells in DHI milk samples can enhance the prognosis of whether an antibiotic treatment of clinical mastitis might be promising or not. Prospectively, this tool may be integrated in the DHI tests to facilitate the decision between therapy or culling.
A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
Aim:
The most suitable method for assessment of response to peptide receptor radionuclide therapy (PRRT) of neuroendocrine tumors (NET) is still under debate. In this study we aimed to compare size (RECIST 1.1), density (Choi), Standardized Uptake Value (SUV) and a newly defined ZP combined parameter derived from Somatostatin Receptor (SSR) PET/CT for prediction of both response to PRRT and overall survival (OS).
Material and Methods:
Thirty-four NET patients with progressive disease (F:M 23:11; mean age 61.2 y; SD ± 12) treated with PRRT using either Lu-177 DOTATOC or Lu-177 DOTATATE and imaged with Ga-68 SSR PET/CT approximately 10–12 weeks prior to and after each treatment cycle were retrospectively analyzed. Median duration of follow-up after the first cycle was 63.9 months (range 6.2–86.2). A total of 77 lesions (2–8 per patient) were analyzed. Response assessment was performed according to RECIST 1.1, Choi and modified EORTC (MORE) criteria. In addition, a new parameter named ZP, the product of Hounsfield unit (HU) and SUVmean (Standard Uptake Value) of a tumor lesion, was tested. Further, SUV values (max and mean) of the tumor were normalized to SUV of normal liver parenchyma. Tumor response was defined as CR, PR, or SD. Gold standard for comparison of baseline parameters for prediction of response of individual target lesions to PRRT was change in size of lesions according to RECIST 1.1. For prediction of overall survival, the response after the first and second PRRT were tested.
Results:
Based on RECIST 1.1, Choi, MORE, and ZP, 85.3%, 64.7%, 61.8%, and 70.6% achieved a response whereas 14.7%, 35.3%, 38.2%, and 29.4% demonstrated PD (progressive disease), respectively. Baseline ZP and ZPnormalized were found to be the only parameters predictive of lesion progression after three PRRT cycles (AUC ZP 0.753; 95% CI 0.6–0.9, p 0.037; AUC ZPnormalized 0.766; 95% CI 0.6–0.9; p 0.029). Based on a cut-off-value of 1201, ZP achieved a sensitivity of 86% and a specificity of 67%, while ZPnormalized reached a sensitivity of 86% and a specificity of 76% at a cut-off-value of 198. Median OS in the total cohort was not reached. In univariate analysis amongst all parameters, only patients having progressive disease according to MORE after the second cycle of PRRT were found to have significantly shorter overall survival (median OS in objective responders not reached, in PD 29.2 months; p 0.015). Patients progressive after two cycles of PRRT according to ZP had shorter OS compared to those responding (median OS for responders not reached, for PD 47.2 months, p 0.066).
Conclusions:
In this explorative study, we showed that Choi, RECIST 1.1, and SUVmax-based response evaluation varied significantly from each other. Only patients showing progressive disease after two PRRT cycles according to MORE criteria had a worse prognosis while baseline ZP and
ZPnormalized performed best in predicting lesion progression after three cycles of PRRT.
Continuous Fiber-Reinforced Material Extrusion with Hybrid Composites of Carbon and Aramid Fibers
(2022)
An existing challenge in the use of continuous fiber reinforcements in additively manufactured parts is the limited availability of suitable fiber materials. This leads to a reduced adaptability of the mechanical properties to the load case. The increased design freedom of additive manufacturing allows the flexible deposition of fiber strands at defined positions, so that even different fiber materials can be easily combined in a printed part. In this work, therefore, an approach is taken to combine carbon and aramid fibers in printed composite parts to investigate their effects on mechanical properties. For this purpose, tensile, flexural and impact tests were performed on printed composite parts made of carbon and aramid fibers in a nylon matrix with five different mixing ratios. The tests showed that the use of hybrid composites for additive manufacturing is a reasonable approach to adapt the mechanical properties to the loading case at hand. The experiments showed that increasing the aramid fiber content resulted in an increase in impact strength, but a decrease in tensile and flexural strength and a decrease in stiffness. Microstructural investigations of the fracture surfaces showed that debonding and delamination were the main failure mechanisms. Finally, Rule of Hybrid Mixture equations were applied to predict the mechanical properties at different mixture ratios. This resulted in predicted values that differed from the experimentally determined values by an average of 5.6%.
Since textual user generated content from social media platforms contains valuable information for decision support and especially corporate credit risk analysis, automated approaches for text classification such as the application of sentiment dictionaries and machine learning algorithms have received great attention in recent user generated content based research endeavors. While machine learning algorithms require individual training data sets for varying sources, sentiment dictionaries can be applied to texts immediately, whereby domain specific dictionaries attain better results than domain independent word lists. We evaluate by means of a literature review how sentiment dictionaries can be constructed for specific domains and languages. Then, we construct nine versions of German sentiment dictionaries relying on a process model which we developed based on the literature review. We apply the dictionaries to a manually classified German language data set from Twitter in which hints for financial (in)stability of companies have been proven. Based on their classification accuracy, we rank the dictionaries and verify their ranking by utilizing Mc Nemar’s test for significance. Our results indicate, that the significantly best dictionary is based on the German language dictionary SentiWortschatz and an extension approach by use of the lexical-semantic database GermaNet. It achieves a classification accuracy of 59,19 % in the underlying three-case-scenario, in which the Tweets are labelled as negative, neutral or positive. A random classification would attain an accuracy of 33,3 % in the same scenario and hence, automated coding by use of the sentiment dictionaries can lead to a reduction of manual efforts. Our process model can be adopted by other researchers when constructing sentiment dictionaries for various domains and languages. Furthermore, our established dictionaries can be used by practitioners especially in the domain of corporate credit risk analysis for automated text classification which has been conducted manually to a great extent up to today.