Basic properties of the two datasets. and respectively represent the number of users, items, ratings and social activities. and denotes the data sparsity of information and social networks respectively.

Journal of business analytics Impact Factor 2024-2025 - ResearchHelpDesk - Business analytics research focuses on developing new insights and a holistic understanding of an organisation’s business environment to help make timely and accurate decisions, and to survive, innovate and grow. Thus, business analytics draws on the full spectrum of descriptive/diagnostic, predictive and prescriptive analytics in order to make better (i.e., data-driven and evidence-based) decisions to create business value in the broadest sense. The mission of the Journal of Business Analytics Journal (JBA) is to serve the emerging and rapidly growing community of business analytics academics and practitioners. We aim to publish articles that use real-world data and cases to tackle problem situations in a creative and innovative manner. We solicit articles that address an interesting research problem, collect and/or repurpose multiple types of data sets, and develop and evaluate analytics methods and methodologies to help organisations apply business analytics in new and novel ways. Reports of research using qualitative or quantitative approaches are welcomed, as are interdisciplinary and mixed methods approaches. Topics may include: Applications of AI and machine learning methods in business analytics Network science and social network applications for business Social media analytics Statistics and econometrics in business analytics Use of novel data science techniques in business analytics Robotics and autonomous vehicles Methods and methodologies for business analytics development and deployment Organisational factors in business analytics Responsible use of business analytics and AI Ethical and social implications of business analytics and AI Bias and explainability in analytics and AI Our editorial philosophy is to publish papers that contribute to theory and practice. Journal of Business Analytics is indexed in: AIS eLibrary Australian Business Deans Council (ABDC) Journal Quality List British Library CLOCKSS Crossref Ei Compendex (Engineering Village) Google Scholar Microsoft Academic Portico SCImago Scopus Ulrich's Periodicals Directory

Feature rank.

Summary of importance and clarity ratings of preliminary set of network reporting recommendations.

The articles with exposure social media were related to the higher citation rates.

The number of citations, mentions of Twitter and other platforms on the articles journal basis.

This dataset was created in the context of the project: " Current trends in scientific research on global warming: A bibliometric analysis (2005-2014)".

Global warming is a topic of increasing public importance, but there have not been published scientometric studies on this topic. The objective of this paper is to contribute to a better understanding of the scientific knowledge in global warming and his effect, as well as to investigate its evolution through the published papers included in Web of Science database. Items under study were collected from Web of Science database from Thomson Reuters. A bibliometric and social network analyses was performed to obtain indicators of scientific productivity, impact and collaboration between researchers, institutions and countries. A subject analysis was also carried out taking into account the key words assigned to papers and subject areas of journals. 1,672 articles were analysed since 2005 until 2014. The most productive journals were Journal of Climate (n=95) and Geophysical Resarch Letters (n=78). The most frequent keywords have been Climate Change (n=722), Model (n=216) and Temperature (n=196). The network of collaboration between countries shows the central position of the United States, together with other leading countries such as United Kingdom, Germany, France and Peoples Republic of China. The research on global warming had grown steadily during the last decade. A vast amount of journals from several subject areas publishes the papers on the topic, including journals of general purpose with high impact factor. Almost all the countries have USA as the main country with which one collaborates. The analysis of key words shows that topics related with climate change, impact, temperature, models and variability are the most important concerns on global warming.

The dataset consist of the following:

1) The list of papers included in the analyses: Papers.xlsx

This file contains 1672 titles, each line representing a paper (including title of the paper, journal ISSN and year of publication).

2) The list of authors: Authors.xlsx

This file contains all 4488 authors, each line representing an author (including full name, total number of papers and year of publication).

3) The list of scientific journals: Journals.xlsx

This file containts all 687 journals, each line representing a journal (including name of the journal, ISSN, total number of papers and year of publication).

4) The list of countries: Country.xlsx

This file contains all 84 countries, each line representing a country (including country name, total number of papers, total number of citations, and number of citations per paper).

5) The list of keywords: Keywords.xlsx

This file contains all 6422 keywords, each line representing a keyword (including keywords, number of papers and year of publication)

Journal of personality and social psychology Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Personality and Social Psychology publishes original papers in all areas of personality and social psychology and emphasizes empirical reports, but may include specialized theoretical, methodological, and review papers. The journal is divided into three independently edited sections. Attitudes and Social Cognition addresses all aspects of psychology (e.g., attitudes, cognition, emotion, motivation) that take place in significant micro- and macrolevel social contexts. Topics include, but are not limited to, attitudes, persuasion, attributions, stereotypes, prejudice, person memory, motivation and self-regulation, communication, social development, cultural processes, and the interplay of moods and emotions with cognition. We accept papers using traditional social-personality psychology methods. However, we also strongly welcome innovative, theory-driven papers that utilize novel methods (e.g., biological methods, neuroscience, large-scale interventions, social network analyses, or "big data" approaches). Papers that are driven by such methods may be processed under a new category of "Innovations in Social Psychology" and potentially handled in an expedited fashion (see Editorial published on-line). All papers will be evaluated with criteria that are consistent with those of the best empirical outlets in social, behavioral, and biological sciences. Interpersonal Relations and Group Processes focuses on the psychology of (interpersonal, intragroup, intergroup) social relations and relationships, whether enduring or fleeting. Submissions may address one type of social relation (e.g., close romantic relationships) or they may address multiple types of social relation (e.g., status within a team and across an institution). Submissions may employ one method or multiple methods. Submissions may examine one context or multiple contexts (e.g., countries, developmental period). Although a multiplicity of methods and contexts will likely be considered a strength, all submissions should address the implications of the chosen method and context for the power and quality of inference. Abstracting and indexing services providing coverage of Journal of Personality and Social Psychology ABI/INFORM Complete ABI/INFORM Professional Advanced Academic OneFile Academic Search Alumni Edition Academic Search Complete Academic Search Elite Academic Search Index Academic Search Premier American Theological Library Association Religion Database ASSIA: Applied Social Sciences Index & Abstracts Business & Company Profile ASAP Business Source Alumni Edition Business Source Complete Business Source Corporate Business Source Corporate Plus Business Source Elite Business Source Index Business Source Premier Cabell's Directory of Publishing Opportunities in Psychology Chartered Association of Business Schools (CABS) Academic Journal Guide Communication & Mass Media Complete Communication Source Current Abstracts Current Contents: Social & Behavioral Sciences EBSCO MegaFILE Educational Research Abstracts Online ERIH (European Reference Index for the Humanities and Social Sciences) Expanded Academic ASAP Family & Society Studies Worldwide General OneFile Higher Education Abstracts Humanities and Social Sciences Index Retrospective IBZ / IBR (Internationale Bibliographie der Rezensionen Geistes- und Sozialwissenschaftlicher Literatur) InfoTrac Custom International Bibliography of the Social Sciences Journal Citations Report: Social Sciences Edition MasterFILE Complete MasterFILE Elite MasterFILE Premier MEDLINE MLA International Bibliography Mosby's Nursing Consult NSA Collection OCLC OmniFile Full Text Mega Professional ProQuest Central ProQuest Central ProQuest Discovery ProQuest Health Management ProQuest Platinum Periodicals ProQuest Psychology Journals ProQuest Public Health ProQuest Research Library ProQuest Social Science Journals Psychology Collection PsycINFO PsycLine Public Affairs Index Race Relations Abstracts RILM Abstracts of Music Literature SafetyLit SCOPUS Social Sciences Abstracts Social Sciences Citation Index Social Sciences Full Text Social Sciences Index Retrospective Social Services Abstracts Social Work Abstracts SocINDEX SocINDEX with Full Text Sociological Abstracts Sociology Source International Studies on Women and Gender Abstracts TOC Premier Women's Studies International

The characteristics of journals.

Big Data and Society Impact Factor 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Introduction

This note describes the data sets used for all analyses contained in the manuscript 'Oxytocin - a social peptide?’[1]

Data Collection

The datasets described here were originally retrieved from Web of Science (WoS) Core Collection via the University of Edinburgh’s library subscription [2]. The aim of the original study for which these data were gathered was to survey peer-reviewed primary studies on oxytocin and social behaviour. To capture relevant papers, we used the following query:

TI = (“oxytocin” OR “pitocin” OR “syntocinon”) AND TS = (“social*” OR “pro$social” OR “anti$social”)

The final search was performed on the 13 September 2021. This returned a total of 2,747 records, of which 2,049 were classified by WoS as ‘articles’. Given our interest in primary studies only – articles reporting original data – we excluded all other document types. We further excluded all articles sub-classified as ‘book chapters’ or as ‘proceeding papers’ in order to limit our analysis to primary studies published in peer-reviewed academic journals. This reduced the set to 1,977 articles. All of these were published in the English language, and no further language refinements were unnecessary.

All available metadata on these 1,977 articles was exported as plain text ‘flat’ format files in four batches, which we later merged together via Notepad++. Upon manually examination, we discovered examples of papers classified as ‘articles’ by WoS that were, in fact, reviews. To further filter our results, we searched all available PMIDs in PubMed (1,903 had associated PMIDs - ~96% of set). We then filtered results to identify all records classified as ‘review’, ‘systematic review’, or ‘meta-analysis’, identifying 75 records [3] (thus, ~4% of records classified by WoS were classified as reviews in PubMed). After examining a sample and agreeing with the PubMed classification, these were removed these from our dataset - leaving a total of 1,902 articles.

From these data, we constructed two datasets via parsing out relevant reference data via the Sci2 Tool [4]. First, we constructed a ‘node-attribute-list’ by first linking unique reference strings (‘Cite Me As’ column in WoS data files) to unique identifiers, we then parsed into this dataset information on the identify of a paper, including the title of the article, all authors, journal publication, year of publication, total citations as recorded from WoS, and WoS accession number. Second, we constructed an ‘edge-list’ that records the citations from a citing paper in the ‘Source’ column and identifies the cited paper in the ‘Target’ column, using the unique identifies as described previously to link these data to the node-attribute-list.

We then constructed a network in which papers are nodes, and citation links between nodes are directed edges between nodes. We used Gephi Version 0.9.2 [5] to manually clean these data by merging duplicate references that are caused by different reference formats or by referencing errors. To do this, we needed to retain both all retrieved records (1,902) as well as including all of their references to papers whether these were included in our original search or not. In total, this produced a network of 46,633 nodes (unique reference strings) and 112,520 edges (citation links). Thus, the average reference list size of these articles is ~59 references. The mean indegree (within network citations) is 2.4 (median is 1) for the entire network reflecting a great diversity in referencing choices among our 1,902 articles.

After merging duplicates, we then restricted the network to include only articles fully retrieved (1,902), and retrained only those that were connected together by citations links in a large interconnected network (i.e. the largest component). In total, 1,892 (99.5%) of our initial set were connected together via citation links, meaning a total of ten papers were removed from the following analysis – and these were neither connected to the largest component, nor did they form connections with one another (i.e. these were ‘isolates’).

This left us with a network of 1,892 nodes connected together by 26,019 edges. It is this network that is described by the ‘node-attribute-list’ and ‘edge-list’ provided here. This network has a mean in-degree of 13.76 (median in-degree of 4). By restricting our analysis in this way, we lose 44,741 unique references (96%) and 86,501 citations (77%) from the full network, but retain a set of articles tightly knitted together, all of which have been fully retrieved due to possessing certain terms related to oxytocin AND social behaviour in their title, abstract, or associated keywords.

Before moving on, we calculated indegree for all nodes in this network – this counts the number of citations to a given paper from other papers within this network – and have included this in the node-attribute-list. We further clustered this network via modularity maximisation via the Leiden algorithm [6]. We set the algorithm to resolution 1, and allowed the algorithm to run over 100 iterations and 100 restarts. This gave Q=0.43 and identified seven clusters, which we describe in detail within the body of the paper. We have included cluster membership as an attribute in the node-attribute-list.

For additional analysis, we also analysed the full reference list data to examine the most commonly cited references between 2016 and 2021 - the results of this are described in OTSOC_Cited_2016-2021.csv. This takes the reference lists of all retrieved papers within the network and examines their full reference lists (including references to other papers not contained within the network). These data were cleaned by matching DOIs and manual cleansing.

Data description

We include here two network datasets: (i) ‘OTSOC-node-attribute-list.csv’ consists of the attributes of 1,892 primary articles retrieved from WoS that include terms indicating a focus on oxytocin and social behaviour; (ii) ‘OTSOC-edge-list.csv’ records the citations between these papers. Together, these can be imported into a range of different software for network analysis; however, we have formatted these for ease of upload into Gephi 0.9.2. Finally, we include (iii) 'OTSOC_Cited_2016-2021' that lists all papers cited by >10 papers in the OTSOC network following any analysis of the bibliographies of retrieved papers. Below, we detail their contents:

1. ‘OTSOC-node-attribute-list.csv’ is a comma-separate values file that contains all node attributes for the citation network (n=1,892) analysed in the paper. The columns refer to:

Id, the unique identifier

Label, the reference string of the paper to which the attributes in this row correspond. This is taken from the ‘Cite Me As’ column from the original WoS download. The reference string is in the following format: last name of first author, publication year, journal, volume, start page, and DOI (if available).

Wos_id, unique Web of Science (WoS) accession number. These can be used to query WoS to find further data on all papers via the ‘UT= ’ field tag.

Title, paper title.

Authors, all named authors.

Journal, journal of publication.

Pub_year, year of publication.

Wos_citations, total number of citations recorded by WoS Core Collection to a given paper as of 13 September 2021

Indegree, the number of within network citations to a given paper, calculated for the network shown in Figure 1 of the manuscript.

Cluster, provides the cluster membership number as discussed within the manuscript (Figure 1). This was established via modularity maximisation via the Leiden algorithm (Res 1; Q=0.43|7 clusters)

2. ‘OTSOC-edge -list.csv’ is a comma-separated values file that contains all citation links between the 1,892 articles (n=26,019). The columns refer to:

Source, the unique identifier of the citing paper.

Target, the unique identifier of the cited paper.

Type, edges are ‘Directed’, and this column tells Gephi to regard all edges as such.

Syr_date, this contains the date of publication of the citing paper.

Tyr_date, this contains the date of publication of the cited paper.

3. 'OTSOC_Cited_2016-2021.csv' is a comma-separated values file that contain citations to all cited references that were cited by at least 10 of the retrieved papers within the OTSOC network published from 2016 onwards. The columns refer to:

Reference, the cited reference string extracted from the bibliographies of retrieved papers.

Publication year, the publication year of the cited reference.

DOI, the DOI of the cited reference.

indegree_2016, the total number of citations to a cited reference from papers published in 2016 and contained within the OTSOC network.

indegree_2017, the total number of citations to a cited reference from papers published in 2017 and contained within the OTSOC network.

indegree_2018, the total number of citations to a cited reference from papers published in 2018 and contained within the OTSOC network.

indegree_2019, the total number of citations to a cited

We report the results of a survey of international relations (IR) scholars on the use of an increasingly common policy designed to close recognition gaps in IR: gender balance in citation (GBC) statements. GBC statements remind and encourage authors submitting work to peer-reviewed outlets to consider the gender balance among the works they cite. We find that these policies enjoyed wide support among IR scholars in our sample countries soon after journals began instituting the policies, but women were more supportive than men of the policies. We also report the results of a question-order experiment that allows us to study how raising awareness of gender gaps in the IR discipline affects the proportion of women that scholars list among the most influential IR scholars in the last 20 years. The effects of exposure to the gender treatment vary, however, by respondents’ gender and whether respondents teach in the United States. The treatment effects were much larger for women than for men in the United States, but the reverse was true outside the United States.

Journal of Chemical Education Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Chemical Education Scope The Journal of Chemical Education (JCM) is the official journal of the Division of Chemical Education of the American Chemical Society, co-published with the American Chemical Society Publications Division. Launched in 1924, the Journal of Chemical Education is the world’s premier chemical education journal. The Journal publishes peer-reviewed articles and related information as a resource to those in the field of chemical education and to those institutions that serve them. JCE typically addresses chemical content, activities, laboratory experiments, instructional methods, and pedagogies. The Journal serves as a means of communication among people across the world who are interested in the teaching and learning of chemistry. This includes instructors of chemistry from middle school through graduate school, professional staff who support these teaching activities, as well as some scientists in commerce, industry, and government. Journal of Chemical Education (JCM) Categories The Journal of Chemical Education publishes: Editorials, Commentaries, and Letters providing a venue for exchanging ideas valuable to the chemical education community. Articles and Communications on many topics relevant to teaching and learning chemistry at all levels, including pedagogical methods and related chemical education research. Activities that explore chemistry concepts with hands-on and often inquiry-based methods, facilitating active learning in classrooms, labs, and informal settings. Demonstrations of chemical phenomena with reliable instructions that educators can emulate to engage students’ interest. Laboratory Experiments that have been successfully used with students to investigate chemical phenomena as well as to develop skills with laboratory techniques, equipment, or instrumentation; notes for instructors and descriptions of hazards allow educators to readily adapt the labs to their teaching objectives and local conditions. Technology Reports describing the use of specific technologies relevant to teaching and learning chemistry with the corresponding software, media, or program files made available through either link to Web sites or as the supporting information of the report. Chemical Education Xchange The Journal of Chemical Education supports the digital learning materials and assets of the Chemical Education Xchange (ChemEd X, www.chemedx.org), published by the ACS Division of Chemical Education. At ChemEd X you will find an award-winning collection of digital videos, references to items of interest from around the Web, and several titles intended to help students learn various aspects of the chemical sciences. ChemEd X offers you the opportunity to share ideas, content, and comment on the world of chemical education in a manner similar to other social Web sites. RG Journal Impact: 1.05 * *This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive. RG Journal impact history 2018 / 2019 1.05 2017 1.43 2016 1.11 2015 1.20 2014 1.13 2013 0.91 2012 0.65 2011 0.44 2010 0.42 2009 0.40 2008 0.36 2007 0.44 2006 0.28 2005 0.25 2004 0.27 2003 0.27 2002 0.28 2001 0.30 2000 0.25 Journal of Chemical Education (JCM) Additional details Cited half-life 0.00 Immediacy index 0.27 Eigenfactor 0.00 Article influence 0.13 Website jchemed.chem.wisc.edu Other titles Pacific Southwest Association of Chemistry Teachers. Proceedings, New England Association of Chemistry Teachers. Report, Journal of chemical education ISSN 0021-9584 OCLC 1754494 Material type Periodical, Internet resource Document type Journal / Magazine / Newspaper, Internet Resource Journal of Chemical Education (JCM) SJR Details Cites Year Value Self Cites 1999 278 Self Cites 2000 282 Self Cites 2001 290 Self Cites 2002 84 Self Cites 2003 275 Self Cites 2004 265 Self Cites 2005 266 Self Cites 2006 256 Self Cites 2007 390 Self Cites 2008 350 Self Cites 2009 301 Self Cites 2010 312 Self Cites 2011 333 Self Cites 2012 353 Self Cites 2013 490 Self Cites 2014 682 Self Cites 2015 831 Self Cites 2016 838 Self Cites 2017 855 Self Cites 2018 853 Self Cites 2019 1149 Total Cites 1999 548 Total Cites 2000 603 Total Cites 2001 551 Total Cites 2002 376 Total Cites 2003 521 Total Cites 2004 469 Total Cites 2005 542 Total Cites 2006 490 Total Cites 2007 752 Total Cites 2008 705 Total Cites 2009 715 Total Cites 2010 739 Total Cites 2011 719 Total Cites 2012 805 Total Cites 2013 1155 Total Cites 2014 1420 Total Cites 2015 1581 Total Cites 2016 1808 Total Cites 2017 1945 Total Cites 2018 2091 Total Cites 2019 2652 Journal of Chemical Education (JCM) International Collaboration Year International Collaboration 1999 4.53 2000 5.60 2001 3.82 2002 1.63 2003 5.78 2004 5.17 2005 5.44 2006 2.88 2007 3.96 2008 4.63 2009 4.45 2010 4.22 2011 6.29 2012 5.42 2013 7.24 2014 5.26 2015 5.25 2016 4.58 2017 6.21 2018 5.96 2019 10.00 Journal of Chemical Education (JCM) Scimago Journal & Country Rank

Journal of Language and Discrimination Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Language and Discrimination - Discrimination is an important research topic in a large number of diverse but related fields, including linguistics, law, anthropology, sociology, and psychology. This complex, multidisciplinary research topic often has a strong focus and concern with language. However, at the moment, theorists and practitioners publish their work in different journals, such as Gender and Language, Journal of Language and Sexuality, Disability Studies, and there is little in the way of intellectual crossover or multidisciplinary work. We argue that the Journal of Language and Discrimination will appeal to those who are working on linguistic discrimination across a wide range of fields. The Journal will include original multidisciplinary research papers and reviews from diverse fields, including linguistics, education, law and criminal justice, anthropology, sociology, psychology, feminism, queer theory, disability studies and race studies. Discrimination is often intimately linked to language. Verbal exchanges may be seen to embody discriminatory uses of language, and linguistic features often play an important role in reproducing, maintaining or subverting systems of discrimination. An alleged discriminatory event may, for instance, be played out discursively in legal rulings, print and broadcast media and social media, creating a complex picture of linguistic patterns and discourse strategies. Analyzing the linguistic strategies of such an event allows for a more comprehensive understanding of discrimination and the actors involved, and goes some way towards understanding the impact of discriminatory incidents in context and in society more generally. There is a struggle over language about whose meaning of a term is accepted or who gets to name someone in a particular way, whose perspective is authorized, and it is this struggle over language which will be investigated: the process of naming an event as discriminatory and having that naming authorized, or challenged; the effects of discrimination on individuals and groups; resistance to discrimination. The journal focuses on the shaping effect of language in situations of discrimination, but will also comprise research on language ideology and language-focused discrimination; i.e. discrimination towards a language, or towards users of a particular language variety. The Journal of Language and Discrimination will be able to provide a unique platform to broadcast the diversity and interdisciplinarity of research on language and discrimination, whilst maintaining a unifying focus. As such, it will allow for the development of new understandings and new approaches to the study of language and discrimination.

The 24 journals publishing the most reports on Chagas cardiomyopathy, their impact factor, subject category and ranking in the 2015 Journal Citation Reports; and their country and language of publication.

List of modules detected by BTS method in 25 complex networks.

List of named social media platforms (alphabetically).

This paper uses text data mining to identify long-term developments in tourism academic research from the perspectives of thematic focus, geography, and gender of tourism authorship. Abstracts of papers published in the period of 1970–2017 in high-ranking tourist journals were extracted from the Scopus database and served as data source for the analysis. Fourteen subject areas were identified using the Latent Dirichlet Allocation (LDA) text mining approach. LDA integrated with GIS information allowed to obtain geography distribution and trends of scholarly output, while probabilistic methods of gender identification based on social network data mining were used to track gender dynamics with sufficient confidence. The findings indicate that, while all 14 topics have been prominent from the inception of tourism studies to the present day, the geography of scholarship has notably expanded and the share of female authorship has increased through time and currently almost equals that of male authorship.

(DS = David's scores)Individual consistency between ranking methods.

Topics ranking about events.