Interpreting social media acts. The various meanings of altmetricsStefanie Haustein
Haustein, S. (2015). "Interpreting social media acts. The various meanings of altmetrics"
Presentation at #ASIST2015 #SIGMET15 panel "Self-Presentation in Academia Today: From Peer-Reviewed Publications to Social Media"
https://www.asist.org/SIG/SIGMET/2015/11/09/panel2015/
Scientific Interactions and Research Evaluation: From Bibliometrics to Altmet...Stefanie Haustein
Haustein, S. (2015). Scientific Interactions and Research Evaluation: From Bibliometrics to Altmetrics
Keynote at ISI2015 in Zadar, Croatia
http://isi2015.de/?session=keynote-c-i
Abstract. Since its creation 350 years ago, the scientific peer-reviewed journal has become the central and most important form of scholarly communication in the natural sciences and medicine. Although the digital revolution has facilitated and accelerated the publishing process by moving from print to online, it has not changed the scientific journal and scholarly communication as such. Today publications and citations in peer-reviewed journals are considered as indicators of scientific productivity and impact and used and misused in research evaluation. As scholarly communication is becoming more open and diverse and manuscripts, data, presentations and code are shared online, the altmetrics and open science movement demand the adaption of evaluation practices. Parallels are drawn between the early days of bibliometrics and current altmetrics research highlighting possibilities and limitations of various metrics and warning against adverse effects.
Interpreting social media acts. The various meanings of altmetricsStefanie Haustein
Haustein, S. (2015). "Interpreting social media acts. The various meanings of altmetrics"
Presentation at #ASIST2015 #SIGMET15 panel "Self-Presentation in Academia Today: From Peer-Reviewed Publications to Social Media"
https://www.asist.org/SIG/SIGMET/2015/11/09/panel2015/
Scientific Interactions and Research Evaluation: From Bibliometrics to Altmet...Stefanie Haustein
Haustein, S. (2015). Scientific Interactions and Research Evaluation: From Bibliometrics to Altmetrics
Keynote at ISI2015 in Zadar, Croatia
http://isi2015.de/?session=keynote-c-i
Abstract. Since its creation 350 years ago, the scientific peer-reviewed journal has become the central and most important form of scholarly communication in the natural sciences and medicine. Although the digital revolution has facilitated and accelerated the publishing process by moving from print to online, it has not changed the scientific journal and scholarly communication as such. Today publications and citations in peer-reviewed journals are considered as indicators of scientific productivity and impact and used and misused in research evaluation. As scholarly communication is becoming more open and diverse and manuscripts, data, presentations and code are shared online, the altmetrics and open science movement demand the adaption of evaluation practices. Parallels are drawn between the early days of bibliometrics and current altmetrics research highlighting possibilities and limitations of various metrics and warning against adverse effects.
This presentation is about Scholarly Communications and how it works, what are ways through one can identify right journals for publications and also briefly discusses preprints as an alternative publications space for making the research more open and visible.
The Impact Factor, Eigenfactor, and Altmetrics: From Theory to AnalysisMolly Keener
Altmetrics is an emerging area encompassing broader assessment of scholarly impact through downloads, links, and online conversations to fill gaps in assessing research. Bibliometrics is the traditional form of measuring the impact of scholarly research through citation rates. The Research & Instruction Librarian for Sciences and the Scholarly Communication Librarian at Wake Forest University will compare bibliometrics and altmetrics, and discuss their applications in science information literacy and research assessment in higher education.
This tutorial deals with two software tools: VOSviewer and CitNetExplorer. VOSviewer (www.vosviewer.com) is a freely available tool for constructing and visualizing bibliographic coupling, co-citation, co-authorship, and term co-occurrence networks. These networks can be constructed based on data downloaded from Web of Science or Scopus. CitNetExplorer (www.citnetexplorer.nl) is a freely available tool for analyzing and visualizing citation networks of publications.
The aim of the tutorial is to provide the participants with a basic knowledge of VOSviewer and CitNetExplorer. Given time constraints, it will not be possible to explore the two tools in a fully comprehensive way, but the tutorial will offer a thorough introduction into the most essential features of the tools. This should be sufficient for the participants to perform all basic analyses that can be done using VOSviewer and CitNetExplorer. In addition, it should allow the participants to independently explore the tools in more detail.
The lecturers are Nees Jan van Eck and Ludo Waltman, both affiliated to the Centre for Science and Technology Studies (CWTS) of Leiden University. Nees Jan and Ludo are the developers and VOSviewer and CitNetExplorer, and they therefore have an in-depth knowledge of both software tools. Nees Jan and Ludo regularly organize courses and workshops on VOSviewer and CitNetExplorer (see for instance www.cwts.nl/Bibliometric-Network-Analysis-and-Science-Mapping-Using-VOSviewer), so they have a lot of experience in training people in the use of these tools.
Stephen Pinfield, lead investigator on the AHRC-funded Open-Access Mega-Journals (OAMJ) project, presented the initials results of the OAMJ research looking at the characteristics of open-access mega-journals (and their impact on scholarly communication patterns) last Wednesday at the RLUK conference (9th-11th March 2016) in London.
Further information about the OAMJ project conducted by Sheffield University and Loughborough University can be found at: http://oamj.org/
Follow us on Twitter at: @OAMJ_Project
Poster Presentation for 4:am Altmetrics Conference, Toronto ON, CA and National Institutes of Health Bibliometrics and Assessment Conference, Bethesda MD, US
Accuracy of citation data in Web of Science and ScopusNees Jan van Eck
Presentation at the 16th International Conference on Scientometrics & Informetrics, Wuhan, China, October 19, 2017.
We present a large-scale analysis of the accuracy of citation data in the Web of Science and Scopus databases. The analysis is based on citations given in publications in Elsevier journals. We reveal significant data quality problems for both databases. Missing and incorrect references are important problems in Web of Science. Duplicate publications are a serious problem in Scopus.
Scientometrics and semantic maps for development (Author: Iina Hellsten)Sarah Cummings
This presentation was a preliminary overview of the research being undertaken by Iina Hellsten and Sarah Cummings. It provides a first outline of what we are planning to do.
Dr. Frances Harris from Centre for Earth and Environmental Sciences Research, School of Geography, Geology and the Environment at Kingston University - with areview of approaches to knowledge co-production focused on food, water, energy and environment.
Accelerating research impact using Kudos - EB 2018Kudos
Kudos co-founder David Sommer explains how you can use the FREE toolkit (www.growkudos.com) to maximise the impact of your publications. He provides the content to increasing impact, demonstrates how you can use Kudos to disseminate your work and, critically, measure which channels are most effective for you.
This presentation is about Scholarly Communications and how it works, what are ways through one can identify right journals for publications and also briefly discusses preprints as an alternative publications space for making the research more open and visible.
The Impact Factor, Eigenfactor, and Altmetrics: From Theory to AnalysisMolly Keener
Altmetrics is an emerging area encompassing broader assessment of scholarly impact through downloads, links, and online conversations to fill gaps in assessing research. Bibliometrics is the traditional form of measuring the impact of scholarly research through citation rates. The Research & Instruction Librarian for Sciences and the Scholarly Communication Librarian at Wake Forest University will compare bibliometrics and altmetrics, and discuss their applications in science information literacy and research assessment in higher education.
This tutorial deals with two software tools: VOSviewer and CitNetExplorer. VOSviewer (www.vosviewer.com) is a freely available tool for constructing and visualizing bibliographic coupling, co-citation, co-authorship, and term co-occurrence networks. These networks can be constructed based on data downloaded from Web of Science or Scopus. CitNetExplorer (www.citnetexplorer.nl) is a freely available tool for analyzing and visualizing citation networks of publications.
The aim of the tutorial is to provide the participants with a basic knowledge of VOSviewer and CitNetExplorer. Given time constraints, it will not be possible to explore the two tools in a fully comprehensive way, but the tutorial will offer a thorough introduction into the most essential features of the tools. This should be sufficient for the participants to perform all basic analyses that can be done using VOSviewer and CitNetExplorer. In addition, it should allow the participants to independently explore the tools in more detail.
The lecturers are Nees Jan van Eck and Ludo Waltman, both affiliated to the Centre for Science and Technology Studies (CWTS) of Leiden University. Nees Jan and Ludo are the developers and VOSviewer and CitNetExplorer, and they therefore have an in-depth knowledge of both software tools. Nees Jan and Ludo regularly organize courses and workshops on VOSviewer and CitNetExplorer (see for instance www.cwts.nl/Bibliometric-Network-Analysis-and-Science-Mapping-Using-VOSviewer), so they have a lot of experience in training people in the use of these tools.
Stephen Pinfield, lead investigator on the AHRC-funded Open-Access Mega-Journals (OAMJ) project, presented the initials results of the OAMJ research looking at the characteristics of open-access mega-journals (and their impact on scholarly communication patterns) last Wednesday at the RLUK conference (9th-11th March 2016) in London.
Further information about the OAMJ project conducted by Sheffield University and Loughborough University can be found at: http://oamj.org/
Follow us on Twitter at: @OAMJ_Project
Poster Presentation for 4:am Altmetrics Conference, Toronto ON, CA and National Institutes of Health Bibliometrics and Assessment Conference, Bethesda MD, US
Accuracy of citation data in Web of Science and ScopusNees Jan van Eck
Presentation at the 16th International Conference on Scientometrics & Informetrics, Wuhan, China, October 19, 2017.
We present a large-scale analysis of the accuracy of citation data in the Web of Science and Scopus databases. The analysis is based on citations given in publications in Elsevier journals. We reveal significant data quality problems for both databases. Missing and incorrect references are important problems in Web of Science. Duplicate publications are a serious problem in Scopus.
Scientometrics and semantic maps for development (Author: Iina Hellsten)Sarah Cummings
This presentation was a preliminary overview of the research being undertaken by Iina Hellsten and Sarah Cummings. It provides a first outline of what we are planning to do.
Dr. Frances Harris from Centre for Earth and Environmental Sciences Research, School of Geography, Geology and the Environment at Kingston University - with areview of approaches to knowledge co-production focused on food, water, energy and environment.
Accelerating research impact using Kudos - EB 2018Kudos
Kudos co-founder David Sommer explains how you can use the FREE toolkit (www.growkudos.com) to maximise the impact of your publications. He provides the content to increasing impact, demonstrates how you can use Kudos to disseminate your work and, critically, measure which channels are most effective for you.
Scholarly communicationand evaluation: from bibliometrics to altmetricsStefanie Haustein
presentation at COAR-SPARC Conference 2015, Porto, Portugal, 16 April 2015
Session 4: Assessing Value
Chair: Lars Björnshauge
https://www.coar-repositories.org/community/events/annual-meeting-2015/programme/
Determining cognitive distance between publication portfolios of evaluators a...Jakaria Rahman
When an expert panel evaluates research groups in a discipline specific research evaluation, it is an open question how one can determine the extent to which the panel members are able to evaluate the research groups. The expertise of the panel members should be well-matched with the research groups to ensure the quality and trustworthiness of the evaluation. Panel members who are credible experts in the field are most likely to provide valuable, relevant recommendations and suggestions that should lead to improved research quality. Due to absence of methods to determine the cognitive distance between evaluators and evaluees, this doctoral research leads to the development of informetric methods for expert panel composition. This contributes to the literature by proposing six informetric approaches to measure the match between evaluators and evaluees in a discipline specific research evaluation using their publications as a representation of their expertise.
The thesis is available at http://hdl.handle.net/10067/1481100151162165141
Teresa Swain
4 posts
Re:Topic 7 DQ 1
The GCU dissertation template describes several ways to establish reliability research studies. A researcher increases the statistical power of a quantitative study by increasing the sample size. This reduces the chance that a real effect (rather than an apparent effect brought about by sampling variability) will be overlooked.
Does triangulation offer the qualitative methodologist a similar reduction in the likelihood of overlooking important results? Why or why not?
Statistical power is a term used is studies that employ quantitative method of research as it is concerned with measuring events with objective observations and numerical assignments of data especially when a causal relationship is the focus (Golafshani, 2003). However, qualitative inquiry seeks to understand rather than point to cause or reason. The focus of this approach is to allow the discovery of phenomenon to unfold naturally so that information uncovered in the process can illuminate other, similar concerns where information may be extrapolated to other scenarios (Golafshani, 2003).
Since the researcher is the “instrument” of measure in this type of inquiry, triangulation of data by using a variety of collection sources such as observations, archives, focus groups, documents, and interviews can help strengthen the integrity of the study (Hatch, 2002). Additionally, the researcher can collect diverse views by collaboration with other researchers, peers, colleagues, and/or those with particular expertise so that alternate explanations can be generated using multiple sources, multiple people to find where ideas converge and diverge. Therefore, qualitative research demands more than adequate sample-size, it flourishes in inquiry and depth of probe.
References
Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The Qualitative Report, 8(4), 597-607. Retrieved from http://www.nova.edu/ssss/QR/QR8-4/golafshani.pdf
Hatch, J. A. (2002). Doing Qualitative Research in Education Settings. Albany: State University of New York Press
Gina Anderson
1 posts
Re:Topic 7 DQ 1
Triangulation is the use of several methods and/or data sources to have a robust understanding of the phenomenon one is studying (Carter, Bryant-Lukosius, DiCenso, Blythe, & Neville, 2014). Triangulation can confirm data and ensure data is complete by using multiple methods for one study, comparing data from various sources (Houghton, Casey, Shaw, & Murphy, 2013). Leung (2015) argues that qualitative research is an important part of psycho-social studies but notes that qualitative research is often criticized for lack of quality valuation and strength. Further, Leung (2015) explains that qualitative research’s equivalent to reliability is consistency. Silverman (as cited in Leung, 2015) proposed five approaches in improving the reliability in qualitative research with the following: “Refutational analysis, constant data comparison, comprehen ...
This is a North Central University course (EDR 8205-2) week 2 assignemt: Analyze Non-Experimental (Non-Causal) Correlational Designs. It is written in APA format, has been graded by an instructor (A), and includes references. Most higher-education assignments are submitted to turnitin, so remember to paraphrase. Let us begin.
Indicators of Innovative Research (Klavans, Boyack, Small, Sorensen, Ioannidis)Kevin Boyack
Most people assume that highly cited papers are "innovative". Using survey results we show that most highly cited papers exemplify normal progress rather than innovation. We also attempt to correlate various indicators with those papers classified as innovative by their authors. Most of these correlations are very weak.
The Effect of Radiology Data Mining Software on Departmental Scholarly ActivityEric Hymer
Study present at AUR 2015 conducted by the Department of Radiology at University of Tennessee Medical Center and Mayo Clinic Jacksonville that shows how research publication increased by 4X after using Softek Illuminate data mining software.
Makes the case that we should let metrics do the "heavy lifting" in the UK REF [Research Excellence Framework]. I show that a university-level ranking based on metrics (Microsoft Academic citations for all papers published with the university's affiliation between 2008-2013) correlates at 0.97 with the The REF power rating taken from Research Fortnight’s calculation. Using metrics to distribute research-related funding would free up a staggering amount of time and money and would allow us to come up with more creative and meaningful ways to build in a research quality component in the REF.
Learning analytics adoption in Higher Education: Reviewing six years of exper...Bart Rienties
In this webinar, Prof Bart Rienties will reflect on the process of implementing learning analytics solutions within the UK higher education setting, its implications, and the key lessons learned in the process. The talk will specifically focus on the Open University UK (OU) experience of implementing learning analytics to support its 170k students and 5k staff. Its flagship OU Analyse has been hailed as one of the largest applications of predictive learning analytics at scale for the last five years, making OU one of the leading institutions in learning analytics domain. The talk will reflect on the strong connections between research and practice, educational theory and learning design, scholarship and professional development, and working in multi-disciplinary teams to explain why the OU is at the forefront of implementing learning analytics at scale. At the same time, not all innovations and interventions have worked. During this webinar, Prof Rienties will discuss the lessons learned from implementing learning analytics systems, how learning analytics has been adopted at OU and other UK institutions, and what the implications for higher education might be.
This is a North Central University paper about analyzing emperimental research designs. It is written in APA format, includes references, and is graded an instructor.
Similar to Haustein, S. (2016). Analyzing, measuring and visualizing the success of interdisciplinarity. (20)
Haustein, S. (2017). Temporalité et publication savante : le cycle de vie des...Stefanie Haustein
Haustein, S. (2017, May). Temporalité et publication savante : le cycle de vie des articles en ligne et sur les médias sociaux. Paper presented at the 85e Congrès de l’Acfas, Colloque 16 – Production et transmission des savoirs scientifiques à l’ère du numérique : acteurs, pratiques et outils, 9 May 2017, Montréal (Canada).
http://www.acfas.ca/evenements/congres/programme/85/enjeux-recherche/16/c
Haustein, S. (2017). The evolution of scholarly communication and the reward ...Stefanie Haustein
Haustein, S. (2017, February). The evolution of scholarly communication and the reward system of science. Fourth Annual KnoweScape Conference 2017, 22–24 February 2017, Sofia (Bulgaria). keynote
http://knowescape.org/knowescape2017/
Haustein, S., Smith, E., Mongeon, P., Shu, F., & Larivière, V. (2016): Access...Stefanie Haustein
Conference presentation
Haustein, S., Smith, E., Mongeon, P., Shu, F., & Larivière, V. (2016). Access to global health research. Prevalence and cost of gold and hybrid open access. In Proceedings of the 21st International Conference on Science and Technology Indicators (p. 410–418). Valencia, Spain.
Haustein, Paul-Hus, Sugimoto & Larivière (2016). Is the gender gap in science...Stefanie Haustein
Presentation of Work in Progress (WiP) research at Social Media & Society, 13 July 2016
https://socialmediaandsociety.org
http://sched.co/7G8u
http://sched.co/7G8u
Lés médias sociaux dans la communication et l'évaluation scientifique : résul...Stefanie Haustein
Les médias sociaux et leur introduction dans un contexte académique ont généré de nouvelles opportunités pour les chercheurs de diffuser leur recherche plus rapidement et à une audience plus grande. Twitter, Facebook, ainsi que les plateformes spécialisées comme ResearchGate et Academia.edu, offrent plusieurs possibilités aux chercheurs d’augmenter leur visibilité et celle de leur recherche. Ces plateformes constituent aussi certains défis pour les chercheurs : leur multiplication fait en sorte qu’ils peuvent s’y perdre et entraîner des pertes de temps. Dans certains cas extrêmes, des commentaires inappropriés émis par les chercheurs sur les médias sociaux ont même mené à des licenciements.
Dans un contexte où l’évaluation de la recherche prend une place de plus en plus importante, les activités associées aux contenus savants partagés sur les médias sociaux ont été proposées par certains comme étant des indicateurs de l’impact de ces contenus. Ces indicateurs, appelés «altmetrics» incluent, par exemple, le nombre de tweets, de liens Facebook, de lecteurs sur Mendeley, de mentions dans les blogs, d’évaluations d’experts sur F1000, de vues sur figshare ainsi que de nombreux autres événements en ligne qui se réfèrent aux documents ou acteurs scientifiques. L’idée derrière les altmetrics était de rendre l’évaluation de la recherche plus englobante, d’aller au-delà du nombre de publications et de citations, afin de capturer l’impact social sur le grand public. Ce lien entre médias sociaux et impact social demeure toutefois à prouver.
Cette formation fournira un aperçu des résultats de recherche récents sur les altmetrics et donnera quelques conseils sur l’utilisation professionnelle des médias sociaux dans un contexte académique.
Identifying Twitter audiences: Who is tweeting about scientific papers?Stefanie Haustein
Haustein, S. & Costas, R. (2015). Identifying Twitter audiences: Who is tweeting about scientific papers?
Presentation at METRICS2015 ASIS&T SIG/MET Workshop
https://www.asist.org/SIG/SIGMET/
Rodrigo Costas & Stefanie Haustein: Citation theories and their application t...Stefanie Haustein
Presentation at #2AMconf
Rodrigo Costas, (CWTS-Leiden University, the Netherlands) & Stefanie Haustein (Université de Montréal, Canada)
Related paper: http://arxiv.org/abs/1502.05701
Communities of attention' around journal papers: Who is tweeting about scient...Stefanie Haustein
Work-in-progress presentation at Social Media & Society 2015
Haustein, S., Bowman, T.D. & Costas, R. (2015). Communities of attention' around journal papers: Who is tweeting about scientific publications?
https://socialmediaandsociety.com/
http://smsociety15.sched.org/event/91e44f025248a9f40e64302c12ce567d/edit#.VbfKfBNViko
Background:
‘Altmetrics’ have been introduced as a way to capture scientific output and impact beyond papers and citations based on traces on various social media platforms (Priem, Taraborelli, Groth, & Neylon, 2010), of which Twitter is believed to have a particular potential to reflect societal impact of research. The analysis and application of various altmetrics such as tweets to scientific papers, however, still lack adequate interpretative frameworks mainly because the processes behind the metrics are not yet fully understood. Currently each tweet is counted equally on platforms such as Altmetric.com or ImpactStory and studies tend to ignore user type and tweet content, although tweets have been shown to range from serious discussions to humour and self-promotion to automated mentions (Haustein et al., 2015).
Objective:
Communities of attention around scientific publications on Twitter are identified based on engagement and exposure of users. Engagement is measured as the degree to which the tweet text differs from the title of the tweeted paper. Exposure refers to the potential audience of the tweet as measured by the number of the user’s followers.
Methods:
Publications from 2012 covered by Web of Science were matched to tweets (until June 2014, excluding retweets) recorded by Altmetric.com via DOI resulting in 660,149 tweets, 237,222 tweeted papers, and 125,083 Twitter users. Engagement was calculated based on the dissimilarity between the tweet text (excluding user names and URLs) and the title of the tweeted document. User data (including the number of followers representing exposure) was collected from Altmetric.com and the Twitter API.
Four user categories were defined, classifying users into four quadrants A, B, C and D according to engagement and exposure values above and below the median of the whole dataset (Figure 1). Statistics based on the tweeting behaviour of users were calculated for each of the categories. The connections between 708 users with more than 100 publications based on co-mentions of the same papers were visualized in a network graph in Figure 1.
Results:
Users in the four categories differ according to tweeting behavior (Figure 1). Users in A have the highest mean tweets per day (based on all tweets) and those in D tweet more about scientific papers (typical for bots identified by Haustein et al. (2015)), while users in A and B discuss publications with slightly higher relative citation rates.
When is an article actually published? An analysis of online availability, pu...Stefanie Haustein
Presentation at ISSI2015
Haustein, S., Bowman, T.D. & Costas, R. (2015). When is an article actually published? An analysis of online availability, publication, and indexation dates
Abstract. With the acceleration of scholarly communication in the digital era, the publication year is no longer a sufficient level of time aggregation for bibliometric and social media indicators. Papers are increasingly cited before they have been officially published in a journal issue and mentioned on Twitter within days of online availability. In order to find a suitable proxy for the day of online publication allowing for the computation of more accurate benchmarks and fine-grained citation and social media event windows, various dates are compared for a set of 58,896 papers published by Nature Publishing Group, PLOS, Springer and Wiley-Blackwell in 2012. Dates include the online date provided by the publishers, the month of the journal issue, the Web of Science indexing date, the date of the first tweet mentioning the paper as well as the Altmetric.com publication and first-seen dates. Comparing these dates, the analysis reveals that large differences exist between publishers, leading to the conclusion that more transparency and standardization is needed in the reporting of publication dates. The date on which the fixed journal article (Version of Record) is first made available on the publisher's website is proposed as a consistent definition of the online date.
Altmetrics: opportunités et défis associés à l’usage des médias sociaux dans ...Stefanie Haustein
350 ans après sa création, la revue savante demeure le principal moyen de diffusion des connaissances savantes, et les citations reçues par les articles constituent la mesure principale de leur impact scientifique. Les médias sociaux et leur introduction dans un contexte académique ont généré de nouvelles opportunités pour capturer l’impact sur un public potentiellement plus large—pas simplement les auteurs qui citent—et plus rapide, compte tenu de la vitesse avec laquelle l’activité dans les médias sociaux peut être mesurée. Le nombre de tweets, de publications Facebook, de lecteurs sur Mendeley, d’évaluations d’experts sur F1000, et de vues sur Slideshare sont des exemples d’indicateurs considérés comme des «altmetrics». De nombreuses revues fournissent également les «altmetrics» associées à chacun de leurs articles, certains chercheurs les présentent sur leurs CVs, et certains organismes subventionnaires commencent à envisager leur utilisation. Même s’il est devenu évident que ces nouvelles mesures sont très hétérogènes et ne peuvent remplacer les citations, on sait encore peu de choses sur leur signification et le type d’impact qu’ils reflètent. Cette communication fera un tour d’horizon des opportunités et des défis associés à l’utilisation de médias sociaux dans la communication savante.
Mendeley as a Source of Readership by Students and Postdocs? Evaluating Ar...Stefanie Haustein
Stefanie Haustein & Vincent Larivière (2014). Mendeley as a Source of Readership by Students and Postdocs? Evaluating Article Usage by Academic Status. Presentation at IATUL 2014. http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=2033&context=iatul
Automated arXiv feeds on Twitter:On the role of bots in scholarly communicationStefanie Haustein
Stefanie Haustein, Kim Holmberg, Timothy D. Bowman, Andrew Tsou, Cassidy R. Sugimoto & Vincent Larivière (2014).
Automated arXiv feeds on Twitter: On the role of bots in scholarly communication
Presentation at 19th Nordic Workshop on Bibliometrics and Research Policy, Reykjavik, 25. September 2014
http://www.rannis.is/bibliometrics/workshop-programme/
The heterogeneity of social media metrics and its effects on statisticsStefanie Haustein
Rodrigo Costas, Stefanie Haustein & Vincent Larivière (2014). The heterogeneity of social media metrics and its effects on statistics.
Presentation at 19th Nordic Workshop on Bibliometrics and Research Policy, Reykjavik, 25. September 2014
http://www.rannis.is/bibliometrics/workshop-programme/
Empirical analyses of scientific papers and researchers on Twitter: Results...Stefanie Haustein
presentation held at PLoS ALM Workshop 2013 in San Francisco
http://article-level-metrics.plos.org/alm-workshop-2013-preliminary-program/
presenting results of two Twitter studies: 1.4 PubMed papers and 37 astrophysicists on Twitter
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
2. Interdisciplinarity
• Integration of data, methods and theories of disciplines
• Expected to derive results greater than the sum of its
disciplinary parts
• Central in science policy and research evaluation
Operationalization in bibliometrics
• Measured by co-citations
• Conflicting evidence regarding citation impact:
• lower citation impact
• higher citation impact
• no significant difference
Introduction
(e.g., Rinia, van Leeuwen & van Raan, 2002; Levitt & Thelwall, 2008; Larivière & Gingras, 2010)
(e.g., Adams, Jackson & Marshall, 2007)
(e.g., Larivière & Gingras, 2010; Uzzi et al., 2013; Yegros-Yegros, Rafols, & D’Este, 2015)
3. Are interdisciplinary long-distance relationships worth
the effort?
• Does an interdisciplinary knowledge base increase
the citation impact of an article?
• Which combinations of subdisciplines lead to the
highest citation impact?
• How does the distance between co-cited
subdisciplines influence citation impact?
Research Questions
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
4. UCSD Map of Science
Dataset and Methods
Börner, K., Klavans, R., Patek, M., Zoss, A. M., Biberstine, J. R., Light, R. P., … Boyack, K. W. (2012). Design and Update of a Classification
System: The UCSD Map of Science. PLoS ONE, 7(7), e39464.
• 14 disciplines
• 544 subdisciplines
5. Dataset and Methods
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
11.1 million articles
2000-2012
6. Dataset and Methods
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
co-cited
Molecular
Ecology
Semiconducting
Materials
9.2 million
interdisciplinary articles
Dataset
co-cited
Molecular
Ecology
Molecular
Ecology
1.9 million
disciplinary articles
7. Dataset and Methods
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
≥30 articles
80,997 co-cited
subdiscipline pairs
distance on
the UCSD map
8. Dataset and Methods
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
5
citations
4.0
citations
7.5
citations
5.0/4.0
=1.25
5.0/7.5
=0.67
Expected citation rate in
Molecular Ecology
Expected citation rate in
Semiconducting Material
win lose
Citation impact
9. Results
Larivière, V., Haustein, S., & Börner, K. (2015). Long-Distance Interdisciplinarity Leads to Higher Scientific Impact. PLoS ONE, 10(3), e0122565.
Percentage of pairs
win win70%
win lose27%
lose lose3%
Relativecitationrate
Distance category
near far
Citation impact and distance
10. Results
2,940 (5.19%) of 56,614 win-win edges
node color: discipline │ edge color: mix of adjacent nodes │ labels: subdiscipline with highest number of win-win relationships per
discipline (number and percentage of win-win relationships)
Number of papers citing win-win relationships (≥10,000 citing articles)
11. Results
943 (0.8%) of 113,228 win-win arcs
node color: discipline │ arc color: outgoing node (clock-wise) │ labels: strongest win-win relationships per discipline
(mean relative citation rate)
Relative citation rate of win-win relationships (≥5.0 mean citations)
12. • Co-citing articles from different subdisciplines leads to
above average citation impact.
• The more diverse the knowledge base, the higher the
citation impact.
Findings support assumption that interdisciplinary
research leads to results greater than the sum of its
disciplinary parts.
Conclusions
Molecular Ecology (Biology) and Semiconducting Materials (Math & Physics)
Citation impact of disciplinary papers 60% below world average
In fact: citation impact of a paper rises with the number of disciplines cited
The majority of co-cited interdisciplinarity pairs led to citation rates above world average for the citing papers
impact increases across distance categories
Pairs that appear most frequently (10,000 citing articles), are from neighboring disciplines
Articles from distant pairs are not as frequently co-cited
But when they occur, they obtain extremely high citation impact:
For example: papers (48) that co-cited papers from Child Abuse (Social Science) and Leukemia obtained 27 as many citations as expected in Child Abuse (12 as many as in Leukemia)