Searching for "metrics"

citations bibliometrics

Bertin, M., Atanassova, I., Gingras, Y., & Larivière, V. (2016). The Invariant Distribution of References in Scientific Articles. Journal Of The Association For Information Science & Technology67(1), 164-177. doi:10.1002/asi.23367

from the viewpoint of bibliometrics, how references are distributed along the structure of scientific papers as well as the age of these cited references

Once the sections of articles are realigned to follow the IMRaD sequence, the position of cited references along the text of articles is invariant across all PLoS journals, with the
introduction and discussion accounting for most of the references. It also provides evidence that the age of cited references varies by section, with older references being found in the methods and more recent references in the discussion.

different roles citations have in the scholarly communication process.

more on bibliometrics in this IMS blog

bibliometrics altmetrics

International Benchmarks for Academic Library Use of Bibliometrics & Altmetrics, 2016-17

ID: 3807768 Report August 2016 115 pages Primary Research Group

The report gives detailed data on the use of various bibliometric and altmetric tools such as Google Scholar, Web of Science, Scimago, Plum Analytics

20 predominantly research universities in the USA, continental Europe, the UK, Canada and Australia/New Zealand. Among the survey participants are: Carnegie Mellon, Cambridge University, Universitat Politècnica de Catalunya the University at Albany, the University of Melbourne, Florida State University, the University of Alberta and Victoria University of Wellington

– 50% of the institutions sampled help their researchers to obtain a Thomsen/Reuters Researcher ID.

ResearcherID provides a solution to the author ambiguity problem within the scholarly research community. Each member is assigned a unique identifier to enable researchers to manage their publication lists, track their times cited counts and h-index, identify potential collaborators and avoid author misidentification. In addition, your ResearcherID information integrates with the Web of Science and is ORCID compliant, allowing you to claim and showcase your publications from a single one account. Search the registry to find collaborators, review publication lists and explore how research is used around the world!

– Just 5% of those surveyed use Facebook Insights in their altmetrics efforts.



more on altmetrics in this IMS blog

social media metrics

more on social media and metrics in this IMS blog

social media and altmetrics

Sugimoto, C. R., Work, S., Larivière, V., & Haustein, S. (2016). Scholarly use of social media and altmetrics: a review of the literature. Retrieved from
One of the central issues associated with altmetrics (short for alternative metrics) is the identification of communities engaging with scholarly content on social media (Haustein, Bowman, & Costas, 2015; Neylon, 2014; Tsou, Bowman, Ghazinejad, & Sugimoto, 2015) . It is thus of central importance to understand the uses and users of social media in the context of scholarly communication.
most identify the following major categori es: social networking, social bookmarking, blogging, microblogging, wikis , and media and data sharing (Gu & Widén -Wulff, 2011; Rowlands, Nicholas, Russell, Canty, & Watkinson, 2011; Tenopir et al., 2013) . Some also conside r conferencing, collaborative authoring, scheduling and meeting tools (Rowlands et al., 2011) or RSS and online documents (Gu & Widén -Wulff, 2011; Tenopir et al., 2013) as social media. The landscape of social media, as well as that of altmetrics, is constantly changing and boundaries with othe r online platforms and traditional metrics are fuzzy. Many online platforms cannot be easily classified and more traditional metrics , such as downloads and mentions in policy documents , have been referred to as altmetrics due to data pr ovider policies.
the Use of social media platforms for by researchers is high — ranging from 75 to 80% in large -scale surveys (Rowlands et al., 2011; Tenopir et al., 2013; Van Eperen & Marincola, 2011) .
less than 10% of scholars reported using Twitter (Rowlands et al., 2011) , while 46% used ResearchGate (Van Noorden, 2014) , and more than 55% use d YouTube (Tenopir et al., 2013) —it is necessary to discuss the use of various types of social media separately . Furthermore, there i s a distinction among types of us e, with studies showing higher uses of social media for dissemination, consumption, communication , and promotion (e.g., Arcila -Calderón, Piñuel -Raigada, & Calderín -Cruz, 2013; Van Noorden, 2014) , and fewer instances of use for creation (i.e., using social media to construct scholarship) (British Library et al., 2012; Carpenter, Wetheridge, Tanner, & Smith, 2012; Procter et al., 2010b; Tenopir et al., 2013) .
Frequently mentioned social platforms in scholarly communication research include research -specific tools such as Mendeley, Zotero, CiteULike, BibSonomy, and Connotea (now defunct) as well as general tools such as Delicious and Digg (Hammond, Hannay, Lund, & Scott, 2005; Hull, Pettifer, & Kell, 2008; Priem & Hemminger, 2010; Reher & Haustein, 2010) .
Social data sharing platforms provide an infrastructure to share various types of scholarly objects —including datasets, software code, figures, presentation slides and videos —and for users to interact with these objects (e.g., comment on, favorite, like , and reuse ). Platforms such as Figshare and SlideShare disseminate scholars’ various types of research outputs such as datasets, figures, infographics, documents, videos, posters , or presentation slides (Enis, 2013) and displays views, likes, and shares by other users (Mas -Bleda et al., 2014) . GitHub provides for uploading and stor ing of software code, which allows users to modify and expand existing code (Dabbish, Stuart, Tsay, & Herbsleb, 2012) , which has been shown to lead to enhanced collaboratio n among developers (Thung, Bissyande, Lo, & Jiang, 2013) . As w ith other social data sharing platforms, usage statistics on the number of view and contributions to a project are provided (Kubilius, 2014) . The registry of research data repositories,, ha s indexed more than 1,200 as of May 2015 2 . However, only a few of these repositories (i.e. , Figshare, SlideShare and Github) include social functionalities and have reached a certain level of participation from scholars (e.g., Begel, Bosch, & Storey, 2013; Kubilius, 2014) .
Video provide s yet another genre for social interaction and scholarly communication (Kousha, Thelwall, & Abdoli, 2012; Sugimoto & Thelwall, 2013) . Of the various video sharing platforms, YouTube, launched in 2005, is by far the most popular
A study of UK scholars reports that the majority o f respondents engaged with video for scholarly communication purposes (Tenopir et al., 2013) , yet only 20% have ever created in that genre. Among British PhD students, 17% had used videos and podcasts passively for research, while 8% had actively contributed (British Library et al., 2012) .
Blogs began in the mid -1990s and were considered ubiquitous by the mid- 200 0s (Gillmor, 2006; Hank, 2011; Lenhart & Fox, 2006; Rainie, 2005) . Scholarly blogs emerged during this time with their own neologisms (e.g., blogademia , blawgosphere , bloggership) and body of research (Hank, 2011) and were considered to change the exclusive structure of scholarly communication
Technorati, considered t o be on e of the largest ind ex of blogs, deleted their entire blog directory in 2014 3 . Individual blogs are also subject to abrupt cancellations and deletions, making questionable the degree to which blogging meets the permanence criteria of scholarly commu nication (Hank, 2011) . (RB) — “an aggregator of blog posts referencing peer -reviewed research in a structured manner” (Shema, Bar -Ilan, & Thelwall, 2015, p. 3) — was launched in 2007 and has been a fairly stable structure in the scholarly blogging environment. RB both aggregates and —through the use of the RB icon — credentials scholarly blogs (Shema et al., 2015) . The informality of the genre (Mewburn & Thomson, 2013) and the ability to circumve nt traditional publishing barr iers has led advocates to claim that blogging can invert traditional academic power hierarchies (Walker, 2006) , allow ing people to construct scholarly identities outside of formal institutionalization (Ewins, 2005; Luzón, 2011; Potter, 2012) and democratize the scientific system (Gijón, 2013) . Another positive characteristic of blogs is their “inherently social” nature (Walker, 2006, p. 132) (see also Kjellberg, 2010; Luzón, 2011 ). Scholars have noted the potential for “communal scholarship” (Hendrick, 2012) made by linking and commenting, calling the platform “a new ‘third place’ for academic discourse” (Halavais, 2006, p. 117) . Commenting functionalities were seen as making possible the “shift from public understanding to public engagement with science” (Kouper, 2010, p. 1) .
Studies have also provided evidence of high rate s of blogging among certain subpopulations: for example, approximately one -third of German university staff (Pscheida et al., 2013) and one fifth of UK doctoral students use blogs (Carpenter et al., 2012) .
Academics are not only producers, but also consumers of blogs: a 2007 survey of medical bloggers foundthat the large majority (86%) read blogs to find medical news (Kovic et al., 2008)

Mahrt and Puschmann (2014) , who defined science blogging as “the use of blogs for science communication” (p. 1). It has been similarly likened to a sp ace for public intellectualism (Kirkup, 2010; Walker, 2006) and as a form of activism to combat perceived biased or pseudoscience (Riesch & Mendel, 2014. Yet, there remains a tension between science bloggers and science journalists, with many science journals dismissing the value of science blogs (Colson, 2011)

while there has been anecdotal evidence of the use of blogs in promotion and tenure (e.g., (Podgor, 2006) the consensus seem s to suggest that most institutions do not value blogging as highly as publishing in traditional outlets, or consider blogging as a measure of service rather than research activity (Hendricks, 2010, para. 30) .
Microblogging developed out of a particular blogging practice, wherein bloggers would post small messages or single files on a blog post. Blogs that focused on such “microposts” were then termed “tumblelogs” and were described as “a quick and dirty stream of consciousness” kind of blogging (Kottke, 2005, para. 2)
most popular microblogs are Twitter (launched in 2006), tumblr (launched in 2007), FriendFeed (launched in 2007 and available in several languages), Plurk (launched in 2008 and popular in Taiwan), and Sina Weibo (launched in 2009 and popular in China).
users to follow other users, search tweets by keywords or hashtags, and link to other media or other tweets

Conference chatter (backchanneling) is another widely studied area in the realm of scholarly microblogging. Twitter use at conferences is generally carried out by a minority of participants

Wikis are collaborative content management platforms enabled by web browsers and embedded markup languages.
Wikipedia has been advocated as a replacement for traditional publishing and peer review models (Xia o & Askin, 2012) and pleas have been made to encourage experts to contribute (Rush & Tracy, 2010) . Despite this, contribution rates remain low — likely hindered by the lack of explicit authorship in Wikipedia, a cornerstone of the traditional academic reward system (Black, 2008; Butler, 2008; Callaway, 2010; Whitworth & Friedman, 2009) . Citations to scholarly documents —another critical component in the reward system —are increasingly being found i n Wikiped ia entries (Bould et al., 2014; Park, 2011; Rousidis et al., 2013) , but are no t yet seen as valid impact indicators (Haustein, Peters, Bar -Ilan, et al., 2014) .
The altmetrics manifesto (Priem et al., 2010, para. 1) , altmetrics can serve as filters , which “reflect the broad, rapid impact of scholarship in this burgeoning ecosystem”.
There are also a host of platforms which are being used informally to discuss and rate scholarly material. Reddit, for example, is a general topic platform where users can submit, discuss and rate online content. Historically, mentions of scientific journals on Reddit have been rare (Thelwall, Haustein, et al., 2013) . However, several new subreddits —e.g., science subreddit 4 , Ask Me Anything sessions 5 –have recently been launched, focusing on the discussion of scientific information. Sites like Amazon (Kousha & Thelwall, 2015) and Goodreads (Zuccala, Verleysen, Cornacchia, & Engels, 2015) , which allow users to comment on and rate books, has also been mined as potential source for the compilation of impact indicators
libraries provide services to support researchers’ use of social media tools and metrics (Lapinski, Piwowar, & Priem, 2013; Rodgers & Barbrow, 2013; Roemer & Borchardt, 2013). One example is Mendeley Institutional Edition,, which mines Mendeley documents, annotations, and behavior and provides these data to libraries (Galligan & Dyas -Correia, 2013) . Libraries can use them for collection management, in a manner similar to other usage data, such as COUNTER statistics (Galligan & Dyas -Correia, 2013) .
Factors affecting social media use; age, academic rank and status, gender, discipline, country and language,


more on altmetrics in this IMS blog:

altmetrics in education

Altmetrics: A Practical Guide for Librarians, Researchers and Academics


In scholarly and scientific publishing, altmetrics are non-traditional metrics[2] proposed as an alternative[3] to more traditional citation impact metrics, such as impact factor and h-index.[4] The term altmetrics was proposed in 2010,[1] as a generalization of article level metrics,[5] and has its roots in the #altmetrics hashtag. Although altmetrics are often thought of as metrics about articles, they can be applied to people, journals, books, data sets, presentations, videos, source code repositories, web pages, etc. They are related to Webometrics, which had similar goals but evolved before the social web. Altmetrics did not originally cover citation counts.[6] It also covers other aspects of the impact of a work, such as how many data and knowledge bases refer to it, article views, downloads, or mentions in social media and news media.[7][8]


more on analytics and metrics in education in this IMS blog


games and psychometrics

Could Video Games Measure Skills That Tests Can’t Capture?

applying the mechanics of games to the science of psychometrics — the measurement of the mind.

Scholars like James Paul Gee believe video games actually come much closer to capturing the learning process in action than traditional fill-in-the-bubble tests. My note: Duh...

Schwartz’s theory of assessment focuses on choice. He argues that the ultimate goal of education is to create independent thinkers who make good decisions. And so we need assessments that test how students think, not what they happen to know at a given moment.

more on games and gamification in this IMS blog:

Metrics for Social Media Marketing

Metrics to Improve Your Social Media Marketing

optimize for sharing, click-throughs, signups or even just visits.

arketing strategy is the editorial calendar,” explains Ben Harper in his article, How to Use Data to Improve Your Content Marketing Strategy


related articles in this blog:

storytelling meets fake news

‘School For Good And Evil’ Is A Kids’ Fantasy Series For The Fake News Era

September 18, 20174:45 PM ET

There’s a YouTube channel, an interactive website with t-shirt giveaways and character contests, Instagrams, dramatic book trailers. Universal Pictures bought the rights to the series pretty much as soon as the first book was published.

The power of a lie that feels true and drives people’s behavior is at the heart of the book — a theme that feels very now.


NMC Horizon Report 2017 K12

NMC/CoSN Horizon Report 2017 K–12 Edition
p. 16 Growing Focus on Measuring Learning
p. 18 Redesigning Learning Spaces
Biophilic Design for Schools : The innate tendency in human beings to focus on life and lifelike processes is biophilia

p. 20 Coding as a Literacy
Best Coding Tools for High School

p. 24

Significant Challenges Impeding Technology Adoption in K–12 Education
Improving Digital Literacy.
 Schools are charged with developing students’ digital citizenship, ensuring mastery of responsible and appropriate technology use, including online etiquette and digital rights and responsibilities in blended and online learning settings. Due to the multitude of elements comprising digital literacy, it is a challenge for schools to implement a comprehensive and cohesive approach to embedding it in curricula.
Rethinking the Roles of Teachers.
Pre-service teacher training programs are also challenged to equip educators with digital and social–emotional competencies, such as the ability to analyze and use student data, amid other professional requirements to ensure classroom readiness.
p. 28 Improving Digital Literacy
Digital literacy spans across subjects and grades, taking a school-wide effort to embed it in curricula. This can ensure that students are empowered to adapt in a quickly changing world
Education Overview: Digital Literacy Has to Encompass More Than Social Use

What Web Literacy Skills are Missing from Learning Standards? Are current learning standards addressing the essential web literacy skills everyone should know?


web literacy;
alignment of stadards

The American Library Association (ALA) defines digital literacy as “the ability to use information and communication technologies to find, evaluate, create, and communicate or share information, requiring both cognitive and technical skills.” While the ALA’s definition does align to some of the skills in “Participate”, it does not specifically mention the skills related to the “Open Practice.”

The library community’s digital and information literacy standards do not specifically include the coding, revision and remixing of digital content as skills required for creating digital information. Most digital content created for the web is “dynamic,” rather than fixed, and coding and remixing skills are needed to create new content and refresh or repurpose existing content. Leaving out these critical skills ignores the fact that library professionals need to be able to build and contribute online content to the ever-changing Internet.

p. 30 Rethinking the Roles of Teachers

Teachers implementing new games and software learn alongside students, which requires
a degree of risk on the teacher’s part as they try new methods and learn what works
p. 32 Teaching Computational Thinking
p. 36 Sustaining Innovation through Leadership Changes
shift the role of teachers from depositors of knowledge to mentors working alongside students;
p. 38  Important Developments in Educational Technology for K–12 Education
Consumer technologies are tools created for recreational and professional purposes and were not designed, at least initially, for educational use — though they may serve well as learning aids and be quite adaptable for use in schools.
Drones > Real-Time Communication Tools > Robotics > Wearable Technology
Digital strategies are not so much technologies as they are ways of using devices and software to enrich teaching and learning, whether inside or outside the classroom.
> Games and Gamification > Location Intelligence > Makerspaces > Preservation and Conservation Technologies
Enabling technologies are those technologies that have the potential to transform what we expect of our devices and tools. The link to learning in this category is less easy to make, but this group of technologies is where substantive technological innovation begins to be visible. Enabling technologies expand the reach of our tools, making them more capable and useful
Affective Computing > Analytics Technologies > Artificial Intelligence > Dynamic Spectrum and TV White Spaces > Electrovibration > Flexible Displays > Mesh Networks > Mobile Broadband > Natural User Interfaces > Near Field Communication > Next Generation Batteries > Open Hardware > Software-Defined Networking > Speech-to-Speech Translation > Virtual Assistants > Wireless Powe
Internet technologies include techniques and essential infrastructure that help to make the technologies underlying how we interact with the network more transparent, less obtrusive, and easier to use.
Bibliometrics and Citation Technologies > Blockchain > Digital Scholarship Technologies > Internet of Things > Syndication Tools
Learning technologies include both tools and resources developed expressly for the education sector, as well as pathways of development that may include tools adapted from other purposes that are matched with strategies to make them useful for learning.
Adaptive Learning Technologies > Microlearning Technologies > Mobile Learning > Online Learning > Virtual and Remote Laboratories
Social media technologies could have been subsumed under the consumer technology category, but they have become so ever-present and so widely used in every part of society that they have been elevated to their own category.
Crowdsourcing > Online Identity > Social Networks > Virtual Worlds
Visualization technologies run the gamut from simple infographics to complex forms of visual data analysis
3D Printing > GIS/Mapping > Information Visualization > Mixed Reality > Virtual Reality
p. 46 Virtual Reality
p. 48 AI
p. 50 IoT

more on NMC Horizon Reports in this IMS blog

fake news and video

Computer Scientists Demonstrate The Potential For Faking Video

As a team out of the University of Washington explains in a new paper titled “Synthesizing Obama: Learning Lip Sync from Audio,” they’ve made several fake videos of Obama.



Fake news: you ain’t seen nothing yet

Generating convincing audio and video of fake events, July 1, 2017

took only a few days to create the clip on a desktop computer using a generative adversarial network (GAN), a type of machine-learning algorithm.

Faith in written information is under attack in some quarters by the spread of what is loosely known as “fake news”. But images and sound recordings retain for many an inherent trustworthiness. GANs are part of a technological wave that threatens this credibility.

Amnesty International is already grappling with some of these issues. Its Citizen Evidence Lab verifies videos and images of alleged human-rights abuses. It uses Google Earth to examine background landscapes and to test whether a video or image was captured when and where it claims. It uses Wolfram Alpha, a search engine, to cross-reference historical weather conditions against those claimed in the video. Amnesty’s work mostly catches old videos that are being labelled as a new atrocity, but it will have to watch out for generated video, too. Cryptography could also help to verify that content has come from a trusted organisation. Media could be signed with a unique key that only the signing organisation—or the originating device—possesses.

more on fake news in this IMS blog

1 2 3 4