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Altmetrics: Listening & Giving Voice
to Ideas with Social Media Data
Anatoliy Gruzd, PhD
Canada Research Chair and Associa...
Should scholarly use of social media be considered
towards tenure and/or promotion?
Gruzd, A., Staves, K., and Wilk, A. (2...
This is what academics
say about Altmetrics on
Twitter
6 years later…
This is what academics
say about Altmetrics on
Twitter
6 years later…
How did we
get here?
Evolution in Scholarly
Communication Channels
Letters
Emails
Mailing lists
Social Media
Scholarly Communication: Then and Now
Letters of Edwin Gilpin, a mining engineer,
government official & author (1850-1907)...
Popular Social Media Sites among Academics
Frequent
Use
Non-academic
soc.networks
Blogs
Online
document
management
Media
r...
Benefits of Using Social Media
0% 10% 20% 30% 40% 50% 60%
Discovering new funding
Garnering mass media attention
Publishin...
Related benefits of social media use
based on the factor analysis
Social & Info
Dissemination
Information
Gathering
Collab...
Who talks about research
on social media?
• Not just academics! But also
• institutions
• journalists
• librarians
• polic...
Unexpected Receptor
Communities
As more people talk about research online, social
‘signals’ are becoming more valuable for …
• Academics – discover what p...
Example: Libraries & Museums
Making Biodiversity Heritage Library (BHL)
collections more “social”!
Google Trends for “Altmetrics” and “Altmetric”
Altmetrics is …
A set of “metrics proposed as an
alternative to the widely ...
Research on Altmetrics is growing… but still very young
Top 10 most prolific scholars in this area
Source: Web of Science,...
Altmetrics: Research Topics
Common research questions:
• To what extent articles published in a journal
are discussed on s...
Altmetrics: Data Providers, Aggregators and Metrics
Data
Providers
Aggregators Metrics
Altmetrics: Data Providers, Aggregators and Metrics
Data
Providers
Aggregators Metrics
Altmetrics: Data Providers
Twitter
68%
Facebook
17%
Blogs
7%
News
6%
Google+
2%
% COVERAGE OF PUBLICATIONS IN SOCIAL MEDIA...
Altmetrics: Data Providers
Lack of APIs for some prominent SN platforms
Researchgate.net Academia.edu
Altmetrics: Data Providers
Lack of attention to some other SN platforms
Reddit
(Kumar et al., 2018)
Content Type n=1,227 p...
Altmetrics: Data Providers, Aggregators and Metrics
Data
Providers
Aggregators Metrics
Altmetrics: Data Aggregators
(Melero, 2015)
NISO Alternative Assessment Project
http://www.niso.org/apps/group_public/document.php?document_id=17090
transparency
repl...
NISO Alternative Assessment Project
http://www.niso.org/apps/group_public/document.php?document_id=17090
Altmetrics:
Data ...
Altmetrics: Data Providers, Aggregators and Metrics
Data
Providers
Aggregators Metrics
Altmetrics: Metrics
Examples based on a case study of measuring impact of a drug safety article published by the
Canadian ...
Altmetrics: Metrics Example
Who tweeted about the CNODES paper?
Twitter user type # users % users
Members of the public 22...
Altmetrics: Developing Metrics based on Social Network
Analysis (SNA)
Nodes = Social Media Users
Ties (lines) = Interactio...
• ~10% of the 3,005 blogs
analyzed cite at least 1
article from the dataset of
2,246 articles.
• The most influential blog...
The Rise of Social Bots
• Who are we studying:
Humans or Bots?
Social Bot – software designed
to act on the Internet with
...
Different Types of Bots
Free music,
games, books,
downloads
Jewelery,
electronics,
vehicles
Contest,
gambling,
prizes
Fina...
Detecting Bots…
Detecting Bots…
Photo
• Color & Edge
histograms
• Color & Edge
Directivity
Descriptor
(CEDD)
• Image
Similarity
Message
• ...
How to introduce these emerging
techniques to altmetrics researchers
and developers who are relying on
social media as the...
Altmetrics: Challenges &
Opportunities!
• Lack of access to some data providers
• Mostly tracking social mentions based on...
Altmetrics: Listening & Giving Voice to
Ideas with Social Media Data
Anatoliy Gruzd, PhD
Canada Research Chair and Associa...
References
• Grier, C., Thomas, K., Paxson, V., & Zhang, M. (2010). @spam: the underground on 140 characters or less (p. 2...
Altmetrics: Listening & Giving Voice to Ideas with Social Media Data
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Altmetrics: Listening & Giving Voice to Ideas with Social Media Data

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Keynote address by Anatoliy Gruzd at the 2017 Altmetrics Conference in Toronto, Canada (Sep 27, 2017)

Abstract
Arguably, even the most innovative ideas take time to catch on. Ideas that seem obvious today, at one point were obscure oddities known only to a select few. Washing your hands, airbags in cars, the internet - none of these ideas were accepted immediately. New ideas need time to incubate, the process of switching from old ideas to new is not seamless nor is it linear. In today’s social media-connected world, even though ideas can spread quickly and more efficiently than ever before, they are now competing for attention with a multitude of other ideas, memes, tweets, snaps, YouTube videos and news (fake and real). Conceptually, if social media is a network of highways on which ideas and people travel, altmetrics are the billboard or traffic signs on these highways that can help interested parties to discover new ideas or re-discover ideas left on the side of the road. While often neglected, the above metaphor is meant to illuminate the important role of altmetrics for researchers, innovators and funders seeking to track the impacts of new ideas, as well as for the many idea consumers looking for emerging and novel insights.
This talk will outline the current state of altmetrics research and how altmetrics are being commonly calculated and used by different stakeholders. It will also explore the social network properties of ideas and how these properties might be used to customize altmetrics for different audiences and uses. The keynote will conclude by calling for the development of training strategies to provide learning opportunities for researchers and administrators from various fields to acquire necessary digital literacy skills so that they better understand how altmetrics are measured and how they can be interpreted for decision making. The keynote will also call on altmetrics developers and researchers to create algorithms and data collection strategies that are less prone to manipulation by the rapid rise of social bots.

Published in: Data & Analytics
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Altmetrics: Listening & Giving Voice to Ideas with Social Media Data

  1. 1. Altmetrics: Listening & Giving Voice to Ideas with Social Media Data Anatoliy Gruzd, PhD Canada Research Chair and Associate Professor Director of Research, Social Media Lab Ryerson University, Toronto, Canada @Gruzd Gruzd@Ryerson.ca
  2. 2. Should scholarly use of social media be considered towards tenure and/or promotion? Gruzd, A., Staves, K., and Wilk, A. (2011). Tenure and Promotion in the Age of Online Social Media. Proceedings of the American Society for Information Science and Technology (ASIS&T) Conference. Back in 2011 …
  3. 3. This is what academics say about Altmetrics on Twitter 6 years later…
  4. 4. This is what academics say about Altmetrics on Twitter 6 years later…
  5. 5. How did we get here?
  6. 6. Evolution in Scholarly Communication Channels Letters Emails Mailing lists Social Media
  7. 7. Scholarly Communication: Then and Now Letters of Edwin Gilpin, a mining engineer, government official & author (1850-1907) Tweets of a contemporary scientist in the domain of Earth Sciences (2014) MacDonald, B., Duggan, L., Gruzd, A, & Collins, V., Scientific Communication: Testing Historical & Present-Day Communication Networks with Social Network Analysis. Working paper. 9 months | 1300 letters | people=616 | ties=1277 1 month | 1302 tweets | people=756 | ties=1578
  8. 8. Popular Social Media Sites among Academics Frequent Use Non-academic soc.networks Blogs Online document management Media repositories Wikis Occasional Use Presentation sharing sites Video/tele conference Blog Wikis Academic soc.networks Gruzd, A., & Goertzen, M. (2013). Wired Academia: Why Social Science Scholars Are Using Social Media. The 46th Hawaii International Conference on System Sciences (HICSS): 3332-3341, DOI: 10.1109/HICSS.2013.614
  9. 9. Benefits of Using Social Media 0% 10% 20% 30% 40% 50% 60% Discovering new funding Garnering mass media attention Publishing findings Maintaining professional image Soliciting advice from peers Collaborating with other researchers Making new research contacts Promoting current work/research Discovering new ideas or publications Following other researchers' work Keeping up to date with topics Gruzd, A., & Goertzen, M. (2013). Wired Academia: Why Social Science Scholars Are Using Social Media. The 46th Hawaii International Conference on System Sciences (HICSS): 3332-3341, DOI: 10.1109/HICSS.2013.614
  10. 10. Related benefits of social media use based on the factor analysis Social & Info Dissemination Information Gathering Collaboration explains 24% of the total variance explains 16% of the total variance
  11. 11. Who talks about research on social media? • Not just academics! But also • institutions • journalists • librarians • policy makers • other groups
  12. 12. Unexpected Receptor Communities
  13. 13. As more people talk about research online, social ‘signals’ are becoming more valuable for … • Academics – discover what peers are discussing • Institutions & Funders –assess research impact • Publishers - ↑readership, feature most-discussed research, discover popular topics for future calls • ATP Committees – evaluate scholarly output / service- component
  14. 14. Example: Libraries & Museums Making Biodiversity Heritage Library (BHL) collections more “social”!
  15. 15. Google Trends for “Altmetrics” and “Altmetric” Altmetrics is … A set of “metrics proposed as an alternative to the widely used journal impact factor and personal citation indices, like the h-index” (Wikipedia) “Study and use of scholarly impact measures based on activity in online tools and environments” (Priem, 2014) “The creation and study of new metrics based on the Social Web for analyzing and informing scholarship” (Adie & Roe, 2013)
  16. 16. Research on Altmetrics is growing… but still very young Top 10 most prolific scholars in this area Source: Web of Science, Sep 2017
  17. 17. Altmetrics: Research Topics Common research questions: • To what extent articles published in a journal are discussed on social media (coverage)? • Is there a relationship between altmetrics and more traditional impact factors (correlation studies)? Ex: among altmetrics, blog count is the strongest predictor of increased citations: • “One more blog post discussing a publication increases the chance of more citations by 4.7%” (Hassan et al., 2017) • Very discipline specific • Recent review paper: Sugimoto et al., 2017
  18. 18. Altmetrics: Data Providers, Aggregators and Metrics Data Providers Aggregators Metrics
  19. 19. Altmetrics: Data Providers, Aggregators and Metrics Data Providers Aggregators Metrics
  20. 20. Altmetrics: Data Providers Twitter 68% Facebook 17% Blogs 7% News 6% Google+ 2% % COVERAGE OF PUBLICATIONS IN SOCIAL MEDIA * Based on ~1M articles published between 2011-2015 (indexed by Scopus) and that have at least one citation & one social media mention (captured up until Feb 2017)(Hassan et al., 2017)
  21. 21. Altmetrics: Data Providers Lack of APIs for some prominent SN platforms Researchgate.net Academia.edu
  22. 22. Altmetrics: Data Providers Lack of attention to some other SN platforms Reddit (Kumar et al., 2018) Content Type n=1,227 posts (100%) Explanation 592 (48%) Information Seeking 274 (22%) Providing Resources 260 (21%) Socializing with Positive Intent 204 (17%) Explanation with Disagreement 71 (6%) Subreddit Rules and Norms 66 (5%) Explanation with Agreement 45 (4%) Socializing with Negative Intent 4 (0%)
  23. 23. Altmetrics: Data Providers, Aggregators and Metrics Data Providers Aggregators Metrics
  24. 24. Altmetrics: Data Aggregators (Melero, 2015)
  25. 25. NISO Alternative Assessment Project http://www.niso.org/apps/group_public/document.php?document_id=17090 transparency replicability accuracy Altmetrics: Data Aggregators
  26. 26. NISO Alternative Assessment Project http://www.niso.org/apps/group_public/document.php?document_id=17090 Altmetrics: Data Aggregators
  27. 27. Altmetrics: Data Providers, Aggregators and Metrics Data Providers Aggregators Metrics
  28. 28. Altmetrics: Metrics Examples based on a case study of measuring impact of a drug safety article published by the Canadian Network for Observational Drug Effect Studies (CNODES) with Gamble, Traynor, Gruzd, Mai, Dormuth, Sketris Basic Indicators
  29. 29. Altmetrics: Metrics Example Who tweeted about the CNODES paper? Twitter user type # users % users Members of the public 22 84% Practitioners (doctors, other healthcare professionals) 3 11% Science communicators (journalists, bloggers, editors) 1 3% Account Type Twitter Account Organization @bcdpic Organization @action_designer Organization @e24Business Individual @social_club_ Individual @Srinjoy Organization @connectcontacts Organization @StartupPortal Individual @kekesimot Organization @youngentre Source: Altrmetric.com
  30. 30. Altmetrics: Developing Metrics based on Social Network Analysis (SNA) Nodes = Social Media Users Ties (lines) = Interactions
  31. 31. • ~10% of the 3,005 blogs analyzed cite at least 1 article from the dataset of 2,246 articles. • The most influential blogs, as measured by in-links, are written by diabetes patients and tend not to cite biomedical literature. Gruzd, A., Black, F.A., Le, Y., Amos, K. (2012). Investigating Biomedical Research Literature in the Blogosphere: A Case Study of Diabetes and HbA1c. Journal of the Medical Library Association 100(1): 34-42. DOI: 10.3163/1536-5050.100.1.007
  32. 32. The Rise of Social Bots • Who are we studying: Humans or Bots? Social Bot – software designed to act on the Internet with some level of autonomy Altmetrics: Metrics - Challenges
  33. 33. Different Types of Bots Free music, games, books, downloads Jewelery, electronics, vehicles Contest, gambling, prizes Finance, loans, realty Increase Twitter following DietAdult (Grier et al, 2010)
  34. 34. Detecting Bots…
  35. 35. Detecting Bots… Photo • Color & Edge histograms • Color & Edge Directivity Descriptor (CEDD) • Image Similarity Message • Sensitive words • URL • Duplicates • #hashtags • @replies Poster • Username • Engagement level • Creation date SocialNetwork • # Friends • # Following • In/out degree centrality • Clustering (Yardi et al, ‘09; Grier et al, ‘10; Wang, ‘10; Jin et al, ’11; Varol et al, ‘17)
  36. 36. How to introduce these emerging techniques to altmetrics researchers and developers who are relying on social media as their go-to data source! The challenge is ... © Chris Allen licensed under Creative Commons
  37. 37. Altmetrics: Challenges & Opportunities! • Lack of access to some data providers • Mostly tracking social mentions based on DOIs/unique identifiers • Reliance on different data providers • Measuring different things • Need for transparency, replicability & accuracy • Noisy data and social bots
  38. 38. Altmetrics: Listening & Giving Voice to Ideas with Social Media Data Anatoliy Gruzd, PhD Canada Research Chair and Associate Professor Director of Research, Social Media Lab Ryerson University, Toronto, Canada @Gruzd Gruzd@Ryerson.ca Slides available at http://bit.ly/4amkey
  39. 39. References • Grier, C., Thomas, K., Paxson, V., & Zhang, M. (2010). @spam: the underground on 140 characters or less (p. 27). ACM Press. http://doi.org/10.1145/1866307.1866311 • Gruzd, A., Black, F.A., Le, Y., Amos, K. (2012). Investigating Biomedical Research Literature in the Blogosphere: A Case Study of Diabetes and HbA1c. Journal of the Medical Library Association 100(1): 34-42. DOI: 10.3163/1536-5050.100.1.007 • Gruzd, A., Staves, K., and Wilk, A. (2011). Tenure and Promotion in the Age of Online Social Media. Proceedings of the American Society for Information Science and Technology (ASIS&T) Conference. • Gurajala, S., White, J. S., Hudson, B., Voter, B. R., & Matthews, J. N. (2016). Profile characteristics of fake Twitter accounts. Big Data & Society, 3(2), 2053951716674236. • Hassan, S. U., Imran, M., Gillani, U., Aljohani, N. R., Bowman, T. D., & Didegah, F. (2017). Measuring social media activity of scientific literature: an exhaustive comparison of scopus and novel altmetrics big data. Scientometrics, 1-21. • Kumar, P., Gruzd, A., Haythornthwaite, C., Gilbert, S., Esteve Del Valle, M., Paulin, D. (2018). Social Media in Educational Practice: Faculty Present and Future Use of Social Media in Teaching. In Proceedings of the 51st Hawaii International Conference on System Sciences. • MacDonald, B., Duggan, L., Gruzd, A, & Collins, V., Scientific Communication: Testing Historical & Present-Day Communication Networks with Social Network Analysis. Working paper. • Melero, R. (2015). Altmetrics–a complement to conventional metrics. Biochemia medica, 25(2), 152-160. • Sugimoto, C. R., Work, S., Larivière, V., & Haustein, S. (2017). Scholarly use of social media and altmetrics: a review of the literature. Journal of the Association for Information Science and Technology, 68(9), 2037-2062. • Varol, O., Ferrara, E., Davis, C. A., Menczer, F., & Flammini, A. (2017). Online human-bot interactions: Detection, estimation, and characterization. arXiv preprint arXiv:1703.03107. • Wang, A. H. (2010). Don’t follow me: Spam detection in Twitter. In Proceedings of the 2010 International Conference on Security and Cryptography (SECRYPT) (pp. 1–10). IEEE.

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