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
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/
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/
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/
Tweet Your Pubs: How Altmetrics are Changing the Way We Measure Research ImpactRobin Featherstone
Presentation given to the Northern Alberta Health Libraries Association (NAHLA) Trends Mini Conference in Edmonton at the University of Alberta on May 2, 2014
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/
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/
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/
Tweet Your Pubs: How Altmetrics are Changing the Way We Measure Research ImpactRobin Featherstone
Presentation given to the Northern Alberta Health Libraries Association (NAHLA) Trends Mini Conference in Edmonton at the University of Alberta on May 2, 2014
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.
E-Learn 2014 Abstract: Today digital footprints are left all over the Internet for others to find. This article reviews the means through which scholars can organize research and connect digital scholarship for increased visibility and impact. A survey of the literature on scholarship tools to provide connections for publishing records, academic citations, and digital identity management was done. The authors reviewed Researcher ID, ORCID, and Google Scholar Citations. The numbers of portals for synthesizing research output and related identity management platforms are increasing; however, understanding what this research impact might look like in the digital age can provide questions for assessment for understanding these traces of scholarship online.
Altmetric: Getting Started with Article-Level MetricsAltmetric
This is a quick-start guide to the insights that may be gained from article-level metrics of scholarly papers. This presentation was authored by Jean Liu (jean@altmetric.com), with data from Euan Adie. Examples from the Altmetric blog (http://www.altmetric.com/blog) are shown. For more information, visit Altmetric (http://www.altmetric.com).
Librarians & altmetrics: Tools, tips and use casesLibrary_Connect
Altmetrics are becoming an integral part of looking at the impact and reach of research. Tracking social and online outlets, altmetrics provide quick feedback from a wide range of sources. In this webinar, library experts will discuss how altmetrics work, tools available, and the application of altmetrics in a range of institutions and for various user groups. Watch the webinar: http://ow.ly/vNeax
Altmetrics are here: are you ready to help your faculty? [ALA Research & Stat...Impactstory Team
Scholarship is changing, along with the way we measure impact. This webinar explores altmetrics and the crucial role librarians have in helping faculty navigate these changes.
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.
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/
Altmetrics - Measuring the impact of scientific activitiesKim Holmberg
An introduction to altmetrics, the complementary metrics of research impact. The presentation covers some of the challenges with more traditional measures, and the potential of and challenges with altmetrics. The presentation gives a brief overview of the background to a new research project about measuring the societal impact of open science.
Insights into Influence: Scholar-Practitioner Profile in the Academy and Comm...Kathleen Reed
Demonstrating knowledge mobilization and accountability are increasingly prominent features of the scholarly landscape; scholar-practitioners need to understand and strategically manage available indicators of impact. At the same time, traditional scholarly metrics and indexing are converging with social media, resulting in new approaches for measuring scholar-practitioner influence. The emerging scene challenges libraries to support scholars, practitioners and students to engage with an evolving environment in which much may be gained or forfeited depending on how reputation is curated. For librarians to assist scholars in this new altmetrics environment, more needs to be known about how students and faculty are or are not engaging with emerging tools available to them. This presentation gives an overview of the considerations, perceptions, and issues related to the use of altmetrics by graduate students and scholar-practitioners at VIU and Royal Roads University.
Presented at Case Western Reserve University to the World Health Interest Group meeting.
Briefly describes how various social media tools can be used within the research lab environment
E-Learn 2014 Abstract: Today digital footprints are left all over the Internet for others to find. This article reviews the means through which scholars can organize research and connect digital scholarship for increased visibility and impact. A survey of the literature on scholarship tools to provide connections for publishing records, academic citations, and digital identity management was done. The authors reviewed Researcher ID, ORCID, and Google Scholar Citations. The numbers of portals for synthesizing research output and related identity management platforms are increasing; however, understanding what this research impact might look like in the digital age can provide questions for assessment for understanding these traces of scholarship online.
Altmetric: Getting Started with Article-Level MetricsAltmetric
This is a quick-start guide to the insights that may be gained from article-level metrics of scholarly papers. This presentation was authored by Jean Liu (jean@altmetric.com), with data from Euan Adie. Examples from the Altmetric blog (http://www.altmetric.com/blog) are shown. For more information, visit Altmetric (http://www.altmetric.com).
Librarians & altmetrics: Tools, tips and use casesLibrary_Connect
Altmetrics are becoming an integral part of looking at the impact and reach of research. Tracking social and online outlets, altmetrics provide quick feedback from a wide range of sources. In this webinar, library experts will discuss how altmetrics work, tools available, and the application of altmetrics in a range of institutions and for various user groups. Watch the webinar: http://ow.ly/vNeax
Altmetrics are here: are you ready to help your faculty? [ALA Research & Stat...Impactstory Team
Scholarship is changing, along with the way we measure impact. This webinar explores altmetrics and the crucial role librarians have in helping faculty navigate these changes.
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.
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/
Altmetrics - Measuring the impact of scientific activitiesKim Holmberg
An introduction to altmetrics, the complementary metrics of research impact. The presentation covers some of the challenges with more traditional measures, and the potential of and challenges with altmetrics. The presentation gives a brief overview of the background to a new research project about measuring the societal impact of open science.
Insights into Influence: Scholar-Practitioner Profile in the Academy and Comm...Kathleen Reed
Demonstrating knowledge mobilization and accountability are increasingly prominent features of the scholarly landscape; scholar-practitioners need to understand and strategically manage available indicators of impact. At the same time, traditional scholarly metrics and indexing are converging with social media, resulting in new approaches for measuring scholar-practitioner influence. The emerging scene challenges libraries to support scholars, practitioners and students to engage with an evolving environment in which much may be gained or forfeited depending on how reputation is curated. For librarians to assist scholars in this new altmetrics environment, more needs to be known about how students and faculty are or are not engaging with emerging tools available to them. This presentation gives an overview of the considerations, perceptions, and issues related to the use of altmetrics by graduate students and scholar-practitioners at VIU and Royal Roads University.
Presented at Case Western Reserve University to the World Health Interest Group meeting.
Briefly describes how various social media tools can be used within the research lab environment
Gender equality means an equal visibility, empowerment, responsibility and participation of women and men in all spheres of public and private life. It also means an equal access to and distribution of resources between women and men and valuing them equally.
Find more:
www.coe.int/equality
gender.equality@coe.int
You Are What You Tweet - Physicians, Professionalism, and Social MediaDavid Marcus
A brief intro to social media and discussion on the way that GME educators should approach SoMe. Delivered at the Lenox Hill Hospital GME Sub-Committee Retreat on March 31st, 2016.
Page 291LEARNING OBJECTIVES· Discuss the issues created by.docxkarlhennesey
Page 291
LEARNING OBJECTIVES
· Discuss the issues created by generalizing research results to other populations, including potential problems using college students as research participants.
· Discuss issues to consider regarding generalization of research results to other cultures and ethnic groups.
· Describe the potential problem of generalizing to other experimenters and suggest possible solutions.
· Discuss the importance of replications, distinguishing between exact replications and conceptual replications.
· Distinguish between narrative literature reviews and meta-analyses.
Page 292IN THIS CHAPTER, WE WILL CONSIDER THE ISSUE OF GENERALIZATION OF RESEARCH FINDINGS. When a single study is conducted with a particular sample and procedure, can the results then be generalized to other populations of research participants, or to other ways of manipulating or measuring the variables? Recall from Chapter 4 that internal validity refers to the ability to infer that there is a causal relationship between variables. External validity is the extent to which findings may be generalized.
GENERALIZING TO OTHER POPULATIONS
Even though a researcher may randomly assign participants to experimental conditions, rarely are participants randomly selected from the general population. As we noted in Chapters 7 and 9, the individuals who participate in psychological research are usually selected because they are available, and the most available population consists of college students—or more specifically, first- and second-year students enrolled in the introductory psychology course to satisfy a general education requirement. They may also be from a particular college or university, may be volunteers, or may be mostly males or mostly females. So, are our research findings limited to these types of subjects, or can we generalize our findings to a more general population? After considering these issues, we will examine the larger issue of culture and how research findings can be generalized to different cultural groups.
College Students
Smart (1966) found that college students were studied in over 70% of the articles published between 1962 and 1964 in the Journal of Experimental Psychology and the Journal of Abnormal and Social Psychology. Sears (1986) reported similar percentages in 1980 and 1985 in a variety of social psychology journals; Arnett (2008) found that 67% of the articles in the 2007 volume of the Journal of Personality and Social Psychology used college student samples. The potential problem is that such studies use a highly restricted population. Sears points out that most of the students are first-year students and sophomores taking the introductory psychology class. They therefore tend to be young and to possess the characteristics of emerging adults: a sense of self-identity that is still developing, social and political attitudes that are in a state of flux, a high need for peer approval, and unstable peer relationships. They are intelligent ...
Gender-based violence is regarded as one of the forms of human rights violation. It is indeed a global phenomenon surpassing all kinds of national, economic, religious, geographic and cultural borders. Woman abuse is usually performed in her direct social environment thereby affecting the physical as well as her mental health. Violence has disastrous consequences on social welfare, children, families and community. Gender violence restricts the woman’s right to be involved in social life.
Presentation by Dr. Mónica I. Feliú-Mójer, Manager of Outreach, Department of Biostatistics, University of Washington, Seattle at open forum discussing the challenges faced by women in science, particularly at the intersection of gender, race and culture.
December 3, 2013, Samuel Kelly Ethnic Cultural Center.
Event co-organized by Mónica I. Feliú-Mójer, Verónica Guajardo and Stephanie Gardner and sponsored by Department of Biostatistics, MESA Community College Program, Louis Stoke Alliance for Minority Participation and School of Public Health, Diversity Committee, all at the University of Washington.
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.
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.
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
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
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
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Haustein, Paul-Hus, Sugimoto & Larivière (2016). Is the gender gap in science mirrored in altmetrics?
1. Stefanie Haustein, Adèle Paul-Hus, Cassidy R. Sugimoto & Vincent Larivière
@stefhaustein
Is the gender gap in science
mirrored in altmetrics?
image from: http://her.yourstory.com/india-global-gender-gap-index-1119
2. Gender Gap in Science
Larivière, V., Ni, C.C., Gingras, Y., Cronin, B., & Sugimoto, C.R. (2013). Global gender disparities in science. Nature, 504(7479), 211–213.
Shen, H. (2013). Inequality quantified: Mind the gender gap. Nature, 495(7439), 22-24.
3. General online population
• Early Internet use heavily male-dominated (Weiser, 2000)
• Increased female participation on social networking sites
(Kimbrough et al., 2013)
• 77% of women, 66% of men in the US use Facebook
2015 (Duggan, 2015)
• 21% of women, 25% of men in the US use Twitter 2015
(Duggan, 2015)
Academics online
• Greater web presence of male academics (van der Weijden &
Calero Medina, 2014)
• Men blog at a greater rate (Shema, Bar-Ilan & Thelwall, 2012)
• More scientific papers are tweeted by men (Tsou, Bowman,
Ghazinejad, & Sugimoto, 2015)
• Social media can flatten academics hierarchies (Veletsianos,
2016)
Gender Gap Online
4. • Does the gender disparity observed for publications
and citations extend to social media?
• Does the visibility of male and female led papers differ
among the following social media platforms:
Research Questions
• Blogs
• Facebook
• Twitter
• Wikipedia
• Mendeley
• Arts
• Biology
• Biomedical Research
• Chemistry
• Clinical Medicine
• Earth & Space
• Engineering & Technology
• Health
• Humanities
• Mathematics
• Physics
• Professional Fields
• Psychology
• Social Sciences
• Does the gender gap in social media visibility of
scholarly journal articles differ by scientific discipline?
5. Dataset and Methods
* based on country-specific first name gender assignment; see Larivière, Ni, Gingras, Cronin, & Sugimoto (2013)
769,695
journal articles
published 2013
blogs
Twitter
Mendeley
Wikipedia
Facebook
gender of
first authors*
• Comparison of female and male first-authored papers by
• social media platform
• discipline
6. Comparing distinct gender distributions
• Coverage
• Mean
• 99th percentile
Confidence intervals based on
bootstrap with replacement
Comparing gender within unified distribution
• Percentile ranks
𝑃𝑖 =
(𝑖 − 0.44)
(𝑛 + 0.12)
Dataset and Methods
n : number of total articles
i : rank if ordered according to social media counts
Gringorten, I.I. (1963). A plotting rule for extreme probability paper. Journal of Geophysical Research, 68, 813–814.
7. Results
• Gender disparities are less pronounced on social media
than for citations
• Results vary by platforms, discipline and indicator
• Coverage
• No difference: 37 / 53%
• Female dominance: 20 / 29%
• Male dominance: 13 / 19%
• Mean
• No difference: 44 / 63%
• Female dominance: 19 / 27%
• Male dominance: 15 / 21%
• 99th percentile
• No difference: 58 / 83%
• Female dominance: 0 / 0%
• Male dominance: 12 / 17%
Percentage of papers
with at least one event
Average number
of events per paper
99th percentile
12. Results
Coverage – differences between social media platforms
• Facebook
• No difference: 9 / 64%
• Female dominance: 2 / 14%
• Male dominance: 3 / 21%
• Mendeley
• No difference: 7 / 50%
• Female dominance: 6 / 43%
• Male dominance: 1 / 7%
• Blogs
• No difference: 8 / 57%
• Female dominance: 1 / 7%
• Male dominance: 5 / 36%
• Twitter
• No difference: 6 / 43%
• Female dominance: 4 / 29%
• Male dominance: 4 / 29%
• Wikipedia
• No difference: 7 / 50%
• Female dominance: 0 / 0%
• Male dominance: 7 / 50%
13. Conclusions
• Gender disparities are less pronounced on social
media than for citations
• Platform and discipline specific differences
Potential of some social media platforms to overcome
traditional hierarchies?
Largely unknown what kind of “impact” is being
measured through mentions of academic papers
Early on, it was much more males online, while social networking sites tend to have a female bias – saw this in the keynote by Susan Halford yesterday; females posting more, reacting more Christoph Lutz
Facebook and Twitter used based on Pew Research Center, 2015
Facebook used more by women and also more intensely
Twitter has a slight male bias
Among Twitter accounts tweeting scientific papers, 66% account holders were male, 28% female
Coverage
Mean
99th percentile
Confidence intervals based onbootstrap with replacement (1,000 iterations)
Various ways to compute percentile ranks, we follow method by Gringorton, as it uses an exponential distribution and the middle publication equals the median
Most gender balanced fields
Explain the percentiles / deciles
0* persentile
Facebook
Facebook used less in a professional context, more flattened hierarchies?
Female: Clinical Medicine, Engineering & Technology
Male: Biology, Chemistry, Physics
Twitter
More male expected, as accounts tweeting academic papers were twice as likely to be maintained by male instead of female users
Gender had not effect on Uses & Gratifiction – Anabel Quan-Haase yesterday
Female: Clinical Medicine, Earth & Space, Professional Fields, Social Sciences
Male: Biology, Biomedical Research, Chemistry, Physics
Mendeley
Due to the academic use and user groups one could assume that similar gender disparities are reflected in Mendeley readership counts as they have been demonstrated to exist in the scientific community. On the other hand, if one assumes that male papers are cited more as they are indeed of higher quality, gender differences might be weaker on Mendeley due to the fact that saving to Mendeley is less selective than citing.
Survey: equal gender distribution – not the general academic population, students
Female: Biology, Clinical Medicine, Earth & Space, Engineering & Technology, Professional Fields, Social Sciences
Male: Chemistry
Blogs
Function as bridge between scientific community and large interested public
Female: Clinical Medicine
Male: Biomedical Research, Chemistry, Health, Physics, Social Sciences
Wikipedia
Clear male focus
Female:
Male: Biology, Biomedical Research, Clinical Medicine, Earth & Space, Humanities, Physics, Psychology
Gender gap less pronounced, however: it’s complicated!
Gaps are less apparent on Facebook and Twitter
Papers with female first authors are more probable to be saved on Mendeley
Wikipedia is clearly male dominated
« Hard science » fields more male dominated than softer sciences