SageBook: Toward a cross-generational social network for the Jewish sages’ prosopography

2018 ◽  
Vol 34 (3) ◽  
pp. 676-695
Author(s):  
Maayan Zhitomirsky-Geffet ◽  
Gila Prebor
Keyword(s):  
Social Network ◽  
Quantitative Analysis ◽  
Large Scale ◽  
Rabbinic Literature ◽  
Jewish Law ◽  
Related Data ◽  
Jewish Thought ◽  
Argumentation Analysis

Abstract In this research we devised and implemented a semi-automatic approach for building a SageBook–a cross-generational social network of the Jewish sages from the Rabbinic literature. The proposed methodology is based on a shallow argumentation analysis leading to detection of lexical–syntactic patterns which represent different relationships between the sages in the text. The method was successfully applied and evaluated on the corpus of the Mishna, the first written work of the Rabbinic Literature which provides the foundation to the Jewish law development. The constructed prosopographical database and the network generated from its data enable a large-scale quantitative analysis of the sages and their related data, and therefore might contribute to the research of the Talmudic literature and evolution of the Jewish thought throughout the two last millennia.

Quality Control of Data in a Large-Scale Cancer Register Program

1966 ◽  
Vol 05 (02) ◽  
pp. 67-74 ◽  
Author(s):  
W. I. Lourie ◽  
W. Haenszeland
Keyword(s):  
United States ◽  
Quality Control ◽  
Cancer Patients ◽  
Large Scale ◽  
The United States ◽  
Newly Diagnosed ◽  
Related Data ◽  
Cancer Register ◽  
Independent Review ◽  
End Results

Quality control of data collected in the United States by the Cancer End Results Program utilizing punchcards prepared by participating registries in accordance with a Uniform Punchcard Code is discussed. Existing arrangements decentralize responsibility for editing and related data processing to the local registries with centralization of tabulating and statistical services in the End Results Section, National Cancer Institute. The most recent deck of punchcards represented over 600,000 cancer patients; approximately 50,000 newly diagnosed cases are added annually.Mechanical editing and inspection of punchcards and field audits are the principal tools for quality control. Mechanical editing of the punchcards includes testing for blank entries and detection of in-admissable or inconsistent codes. Highly improbable codes are subjected to special scrutiny. Field audits include the drawing of a 1-10 percent random sample of punchcards submitted by a registry; the charts are .then reabstracted and recoded by a NCI staff member and differences between the punchcard and the results of independent review are noted.

Mapping the Topics and Evolutions of Chinese Children’s Bestsellers

Libri ◽  
2020 ◽  
Vol 70 (4) ◽  
pp. 305-317
Author(s):  
Jiming Hu ◽  
Xiang Zheng ◽  
Peng Wen ◽  
Jie Xu
Keyword(s):  
Social Network ◽  
Quantitative Analysis ◽  
Network Analysis ◽  
Intellectual Structure ◽  
Structure Evolution ◽  
Children's Books ◽  
Children’S Books ◽  
Correlation Structures ◽  
The World ◽  
Data Source

AbstractChildren’s books involve a large number of topics. Research on them has been paid much attention to by both scholars and practitioners. However, the existing achievements do not focus on China, which is the fastest growing market for children’s books in the world. Studies using quantitative analysis are low in number, especially on the intellectual structure, evolution patterns, and development trends of topics of children’s bestsellers in China. Dangdang.com, the biggest Chinese online bookstore, was chosen as a data source to obtain children’s bestsellers, and topic words in them were extracted from brief introductions. With the aid of co-occurrence theory and tools of social network analysis and visualization, the distribution, correlation structures, and evolution patterns of topics were revealed and visualized. This study shows that topics of Chinese children’s bestsellers are broad and relatively concentrated, but their distribution is unbalanced. There are four distinguished topic communities (Living, Animal, World, and Child) in terms of centrality and maturity, and they all establish their individual systems and tend to be mature. The evolution of these communities tends to be stable with powerful continuity.

scholarly journals EEG Data Quality: Determinants and Impact in a Multicenter Study of Children, Adolescents, and Adults with Attention-Deficit/Hyperactivity Disorder (ADHD)

2021 ◽  
Vol 11 (2) ◽  
pp. 214
Author(s):  
Anna Kaiser ◽  
Pascal-M. Aggensteiner ◽  
Martin Holtmann ◽  
Andreas Fallgatter ◽  
Marcel Romanos ◽  
...  
Keyword(s):  
Data Quality ◽  
Large Scale ◽  
Linear Models ◽  
Spectral Power ◽  
Control Group ◽  
Continuous Performance Task ◽  
Related Data ◽  
Eyes Closed ◽  
Eeg Data ◽  
Eyes Open

Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (ntotal = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.

scholarly journals “Am besten, du gehst.” Zur nähesprachlichen Verwendung des am-Superlativs im Vor-Vorfeld

Glottotheory ◽  
2020 ◽  
Vol 10 (1-2) ◽  
pp. 1-29
Author(s):  
Doris Höhmann
Keyword(s):  
Quantitative Analysis ◽  
Large Scale ◽  
Language Use ◽  
First Approximation ◽  
Core Part

AbstractThis paper investigates the use of the German am-superlative in colloquial utterances such as am besten, du gehst jetzt. In a first approximation, this construction can be described as elliptically used am-superlative occurring on the left sentence periphery within an Operator-Skopus-Struktur (Barden/Elstermann/Fiehler 2001). As will be shown in the empirical core part of the study, a qualitative-quantitative analysis, the pattern appears to be characterized by different overlapping and interplaying tendencies in language use (e.g. the selection and frequency of pronouns and sentence mood). The data used for the qualitative-quantitative analysis is taken mainly from a large-scale web corpus (deTenTen13).

scholarly journals Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146220 ◽  
Author(s):  
Aleksandra do Socorro da Silva ◽  
Silvana Rossy de Brito ◽  
Nandamudi Lankalapalli Vijaykumar ◽  
Cláudio Alex Jorge da Rocha ◽  
Maurílio de Abreu Monteiro ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Large Scale ◽  
Information And Communication

scholarly journals Temporal Activity Path Based Character Correction in Heterogeneous Social Networks via Multimedia Sources

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Large Scale ◽  
Multimedia Data ◽  
Attribute Information ◽  
Novel Method ◽  
Relationship Network ◽  
Heterogeneous Social Networks ◽  
The Relationship ◽  
Over Time

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.

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