This document summarizes a presentation on altmetrics and social media data. It discusses how social media is being used in scholarly communication, providing examples of academics using blogs, wikis and other sites. It also explores emerging altmetric data sources like Twitter, benefits of social media use, and who discusses research online. The document then examines altmetric data providers, aggregators and metrics, addressing challenges around coverage, normalization and social bots. It argues for more research on improving altmetrics methodology.
Anatoliy Gruzd and Philip Mai
Workshop presented at the TTRA Annual International Conference in Quebec City (June 20, 2017)
https://2017ttraannualinternationalconfe.sched.com/event/9yCg/social-listening-how-to-do-it-and-how-to-use-it-veille-sociale-comment-faire-et-comment-lutiliser?iframe=no&w=100%&sidebar=no&bg=no
§ Gruzd, A., Jacobson, J., Dubois, E. (2017). You’re Hired: Examining Acceptance of Social Media Screening of Job Applicants. In Proceedings of the 23rd Americas Conference on Information Systems (AMCIS), August 10-12, 2017, Boston, MA, USA.
Available at http://aisel.aisnet.org/amcis2017/DataScience/Presentations/28/
Abstract:
The paper examines attitudes towards employers using social media to screen job applicants. In an online survey of 454 participants, we compare the comfort level with this practice in relation to different types of information that can be gathered from publicly accessible social media. The results revealed a nuanced nature of people’s information privacy expectations in the context of hiring practices. People’s perceptions of employers using social media to screen job applicants depends on (1) whether or not they are currently seeking employment (or plan to), (2) the type of information that is being accessed by a prospective em-ployer (if there are on the job market), and (3) their cultural background, but not gender. The findings emphasize the need for employers and recruiters who are relying on social media to screen job applicants to be aware of the types of information that may be perceived to be more sensitive by applicants, such as social network-related information.
Keynote at the Second International Symposium on Spatiotemporal Computing (ISSC 2017), August 7th – 9th, 2017 at Harvard University, Cambridge, Massachusetts
Social media is now the place where people are gathering en masse to discuss the news with their friends, neighbors and complete strangers. This change in news consumers’ behavior is proving to be a challenge for local news, but it is also an opportunity. Users and system generated data from social media can also be a boon for content creators. This presentation will feature a case study showing how publishers can use social media analytics to gain insights into their audience and how to use this information to foster a stronger sense of community around their brand of journalism. The case study will focus on how to use Netlytic, a cloud-based social media analytics tool, to mine the public Facebook interactions of the readers of BlogTO, a regional, Canadian-based media outlet, to find out what their readers are interested in and what engages them.
Presentation at the Workshop on "Small Data and Big Data Controversies and Alternatives: Perspectives from The Sage Handbook of Social Media Research Methods" with Anabel Quan-Haase, Luke Sloan, Diane Rasmussen Pennington, et al.
LINK: http://sched.co/7G5N
Abstract:
This article examines how online groups are formed and sustained during crisis periods, especially when political polarization in society is at its highest level. We focus on the use of Vkontakte (VK), a popular social networking site in Ukraine, to understand how it was used by Pro- and Anti-Maidan groups during the 2013/2014 crisis in Ukraine. In particular, we ask whether and to what extent the ideology (or other factors) of a particular group shapes its network structure. We find some support that online social networks are likely to represent local and potentially preexisting social networks, likely due to the dominance of reciprocal (and often close) relationships on VK and opportunities for group members to meet face-to-face during offline protests. We also identify a number of group-level indicators, such as degree centralization, modularity index and average engagement level, that could help to classify groups based on their network properties. Community researchers can start applying these group-level indicators to online communities outside VK; they can also learn from this article how to identify networks of spam and marketing accounts.
Anatoliy Gruzd and Philip Mai
Workshop presented at the TTRA Annual International Conference in Quebec City (June 20, 2017)
https://2017ttraannualinternationalconfe.sched.com/event/9yCg/social-listening-how-to-do-it-and-how-to-use-it-veille-sociale-comment-faire-et-comment-lutiliser?iframe=no&w=100%&sidebar=no&bg=no
§ Gruzd, A., Jacobson, J., Dubois, E. (2017). You’re Hired: Examining Acceptance of Social Media Screening of Job Applicants. In Proceedings of the 23rd Americas Conference on Information Systems (AMCIS), August 10-12, 2017, Boston, MA, USA.
Available at http://aisel.aisnet.org/amcis2017/DataScience/Presentations/28/
Abstract:
The paper examines attitudes towards employers using social media to screen job applicants. In an online survey of 454 participants, we compare the comfort level with this practice in relation to different types of information that can be gathered from publicly accessible social media. The results revealed a nuanced nature of people’s information privacy expectations in the context of hiring practices. People’s perceptions of employers using social media to screen job applicants depends on (1) whether or not they are currently seeking employment (or plan to), (2) the type of information that is being accessed by a prospective em-ployer (if there are on the job market), and (3) their cultural background, but not gender. The findings emphasize the need for employers and recruiters who are relying on social media to screen job applicants to be aware of the types of information that may be perceived to be more sensitive by applicants, such as social network-related information.
Keynote at the Second International Symposium on Spatiotemporal Computing (ISSC 2017), August 7th – 9th, 2017 at Harvard University, Cambridge, Massachusetts
Social media is now the place where people are gathering en masse to discuss the news with their friends, neighbors and complete strangers. This change in news consumers’ behavior is proving to be a challenge for local news, but it is also an opportunity. Users and system generated data from social media can also be a boon for content creators. This presentation will feature a case study showing how publishers can use social media analytics to gain insights into their audience and how to use this information to foster a stronger sense of community around their brand of journalism. The case study will focus on how to use Netlytic, a cloud-based social media analytics tool, to mine the public Facebook interactions of the readers of BlogTO, a regional, Canadian-based media outlet, to find out what their readers are interested in and what engages them.
Presentation at the Workshop on "Small Data and Big Data Controversies and Alternatives: Perspectives from The Sage Handbook of Social Media Research Methods" with Anabel Quan-Haase, Luke Sloan, Diane Rasmussen Pennington, et al.
LINK: http://sched.co/7G5N
Abstract:
This article examines how online groups are formed and sustained during crisis periods, especially when political polarization in society is at its highest level. We focus on the use of Vkontakte (VK), a popular social networking site in Ukraine, to understand how it was used by Pro- and Anti-Maidan groups during the 2013/2014 crisis in Ukraine. In particular, we ask whether and to what extent the ideology (or other factors) of a particular group shapes its network structure. We find some support that online social networks are likely to represent local and potentially preexisting social networks, likely due to the dominance of reciprocal (and often close) relationships on VK and opportunities for group members to meet face-to-face during offline protests. We also identify a number of group-level indicators, such as degree centralization, modularity index and average engagement level, that could help to classify groups based on their network properties. Community researchers can start applying these group-level indicators to online communities outside VK; they can also learn from this article how to identify networks of spam and marketing accounts.
Abstract:
Social media data is a rich source of behavioural data that can reveal how we connect and interact with each other online in real-time and over time, and what that might mean for our society as we continue to speed towards an increasingly computer-mediated future. And as more and more Canadians are joining and contributing to various social media websites, their automatically recorded data are rapidly becoming available to third parties to mine for both commercial and academic purposes. As a result, questions around why and how data consumers’ use social media data are becoming pertinent. This talk will review different approaches to Social Media Data Stewardship (the collection, storage, use, reuse, analysis, and preservation of social media data) and discuss some ethical implications of working with such data.
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
Panel presented as part of the 2017 Data Power Conference (Ottawa, ON, June 23, 2017)
Anatoliy Gruzd (@gruzd), Jenna Jacobson (@jacobsonjenna), Priya Kumar (@link_priya), Philip Mai (@phmai)
Who’s in the Gang? Revealing Coordinating Communities in Social MediaDerek Weber
Political astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Common approaches examining these phenomena focus on broad campaigns rather than the small groups responsible. To reveal networks of cooperating accounts, we propose a novel temporal window approach that relies on account interactions and metadata alone. It detects groups of accounts engaging in behaviours that, in concert, execute different goal-based strategies, which we describe. Our approach is validated against two relevant datasets with ground truth data. See https://github.com/weberdc/find_hccs for code and data.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining).
Co-authored with Frank Neumann (University of Adelaide)
Shareworthiness and Motivated Reasoning in Hyper-Partisan News Sharing Behavi...Axel Bruns
Paper by Magdalena Wischnewski, Axel Bruns, and Tobias Keller, presented at the 2021 International Communication Association conference, 27-31 May 2021.
Researching Social Media – Big Data and Social Media AnalysisFarida Vis
Researching Social Media – Big Data and Social Media Analysis, presentation for the Social Media for Researchers: A Sheffield Universities Social Media Symposium, 23 September 2014
Social Media in Science and Altmetrics - New Ways of Measuring Research Impact Christoph Lutz
Social media are becoming more and more popular in scientific communication. Scientists use them for a range of purposes, from sharing publications, to blogging about their own or others’ research, conference tweeting, interpersonal communication and online participation, for example via Q&As on academic social network sites like ResearchGate and academia.edu. Moreover, many social media platforms can be used for impact measurement via so-called altmetrics. Altmetrics capture and aggregate social media metrics such as (re)tweets, Facebook likes, Mendeley bookmarks and Wikipedia cites. They can challenge or at least complement bibliometric impact measures, like the Journal Impact Factor and the h-index, which have been criticized on various grounds. This presentation first summarizes recent studies on social media adoption in science. It then focuses on altmetrics and summarizes key findings in that domain. Finally, it gives a hands-on introduction to altmetrics by demonstrating two prominent services: Impactstory and Altmetric.com.
WEBINAR: Joining the "buzz": the role of social media in raising research vi...HELIGLIASA
Joining the ‘buzz’ : the role of social media in raising research visibility: Traditional bibliometric methods of evaluating academic research, such as journal impact factors and article citations, have been supplemented in the past 5-10 years by the development of altmetrics (alternative metrics/article level metrics). Altmetrics measures aspects of the impact of a work, such as references in data and knowledge bases, article views, downloads and mentions in social media and news media.
This webinar (based on a presentation of the same name at the LIASA conference on 24th September 2014) gives a brief background to altmetrics and demonstrates how Rhodes University, Grahamstown, librarians are using social media to raise the visibility of the research output of their institution.
Presented by Eileen Shepherd, Principal Librarian, Science & Pharmacy, Rhodes University Library
Abstract:
Social media data is a rich source of behavioural data that can reveal how we connect and interact with each other online in real-time and over time, and what that might mean for our society as we continue to speed towards an increasingly computer-mediated future. And as more and more Canadians are joining and contributing to various social media websites, their automatically recorded data are rapidly becoming available to third parties to mine for both commercial and academic purposes. As a result, questions around why and how data consumers’ use social media data are becoming pertinent. This talk will review different approaches to Social Media Data Stewardship (the collection, storage, use, reuse, analysis, and preservation of social media data) and discuss some ethical implications of working with such data.
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
Panel presented as part of the 2017 Data Power Conference (Ottawa, ON, June 23, 2017)
Anatoliy Gruzd (@gruzd), Jenna Jacobson (@jacobsonjenna), Priya Kumar (@link_priya), Philip Mai (@phmai)
Who’s in the Gang? Revealing Coordinating Communities in Social MediaDerek Weber
Political astroturfing and organised trolling are online malicious behaviours with significant real-world effects. Common approaches examining these phenomena focus on broad campaigns rather than the small groups responsible. To reveal networks of cooperating accounts, we propose a novel temporal window approach that relies on account interactions and metadata alone. It detects groups of accounts engaging in behaviours that, in concert, execute different goal-based strategies, which we describe. Our approach is validated against two relevant datasets with ground truth data. See https://github.com/weberdc/find_hccs for code and data.
Presented at ASONAM'20 (2020 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining).
Co-authored with Frank Neumann (University of Adelaide)
Shareworthiness and Motivated Reasoning in Hyper-Partisan News Sharing Behavi...Axel Bruns
Paper by Magdalena Wischnewski, Axel Bruns, and Tobias Keller, presented at the 2021 International Communication Association conference, 27-31 May 2021.
Researching Social Media – Big Data and Social Media AnalysisFarida Vis
Researching Social Media – Big Data and Social Media Analysis, presentation for the Social Media for Researchers: A Sheffield Universities Social Media Symposium, 23 September 2014
Social Media in Science and Altmetrics - New Ways of Measuring Research Impact Christoph Lutz
Social media are becoming more and more popular in scientific communication. Scientists use them for a range of purposes, from sharing publications, to blogging about their own or others’ research, conference tweeting, interpersonal communication and online participation, for example via Q&As on academic social network sites like ResearchGate and academia.edu. Moreover, many social media platforms can be used for impact measurement via so-called altmetrics. Altmetrics capture and aggregate social media metrics such as (re)tweets, Facebook likes, Mendeley bookmarks and Wikipedia cites. They can challenge or at least complement bibliometric impact measures, like the Journal Impact Factor and the h-index, which have been criticized on various grounds. This presentation first summarizes recent studies on social media adoption in science. It then focuses on altmetrics and summarizes key findings in that domain. Finally, it gives a hands-on introduction to altmetrics by demonstrating two prominent services: Impactstory and Altmetric.com.
WEBINAR: Joining the "buzz": the role of social media in raising research vi...HELIGLIASA
Joining the ‘buzz’ : the role of social media in raising research visibility: Traditional bibliometric methods of evaluating academic research, such as journal impact factors and article citations, have been supplemented in the past 5-10 years by the development of altmetrics (alternative metrics/article level metrics). Altmetrics measures aspects of the impact of a work, such as references in data and knowledge bases, article views, downloads and mentions in social media and news media.
This webinar (based on a presentation of the same name at the LIASA conference on 24th September 2014) gives a brief background to altmetrics and demonstrates how Rhodes University, Grahamstown, librarians are using social media to raise the visibility of the research output of their institution.
Presented by Eileen Shepherd, Principal Librarian, Science & Pharmacy, Rhodes University Library
Joining the ‘buzz’ : the role of social media in raising research visibility ...Eileen Shepherd
[This presentation is based on my previous presentation, of the same title, at the LIASA 2014 conference. It was presented as a webinar for LIASA Higher Education Libraries Interest Group on 6/11/2014]
Traditional bibliometric methods of evaluating academic research, such as journal impact factors and article citations, have been supplemented in the past 5-10 years by the development of altmetrics (alternative metrics or article level metrics). Altmetrics measures impact of research, data and publications, such as references in data and knowledge bases, article views, downloads and mentions in social media and news media. This presentation gives a brief background to altmetrics and demonstrates how Rhodes University librarians are using social media to raise the visibility of the research output of their institution. (Rhodes University is in Grahamstown, South Africa)
Joining the ‘buzz’ : the role of social media in raising research visibility at Rhodes University, Grahamstown, South Africa - HELIG Webinar presented by Eileen Shepherd
Research-Open Access-Social Media: a winning combination, presented by Eileen Shepherd at the Open Access Symposium on 21 October 2014 - Rhodes University Library
Research-Open Access-Social Media: A winning combinationEileen Shepherd
This presentation endeavours to show that social media and open access are a great couple, to provide a brief introduction to altmetrics – a non-traditional form of measuring scholarly impact and to demonstrate the use of social media in raising awareness and visibility of Rhodes University research
Public engagement while you sleep? How altmetrics can help researchers broade...UoLResearchSupport
Slides from a seminar delivered for pepnet at the University of Leeds 28 Nov 2018. Thanks to Charlotte Perry-Houts for extra content:
From peer reviewed journal articles, to assorted reports and grey literature, to datasets comprising numerical, textual or multimedia files; we generate thousands of research outputs.
In this session, Kirsten Thompson (OD&PL) and Nick Sheppard (Library) will discuss strategies for increasing quality online engagement with that research. We will explore how you can use ‘alternative metrics’, more commonly known as ‘altmetrics’, to monitor such engagement. Altmetrics can help to showcase the reach of your work, supplement grant and tenure applications, identify new audiences, and connect with other researchers in your discipline.
In the age of “fake news”, academics have a responsibility to share their expertise beyond the Ivory Tower. We’ll show you how to ensure all these disparate outputs are properly curated in university repositories with a Digital Object Identifier (DOI). There will also be an opportunity to learn about and contribute to the Library led Data Management Engagement Award, a first-ever competition launched to elicit new and imaginative ideas for engaging researchers in the practices of good Research Data Management (RDM).
How altmetrics can help researchers broaden the reach of their work. Workshop facilitated by Kirsten Thompson and Nick Sheppard at the University of Leeds for the #PepnetLeeds network November 28th 2018.
Weller social media as research data_psm15Katrin Weller
Presentation at "Preserving Social Media" (#psm15), London, October 27th 2015.
http://dpconline.org/events/details/96-preserving-socialmedia?xref=126%3ASocialMedia15
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/
How altmetrics can help researchers broaden the reach of their work
Slides from workshop to pepnet (Public Engagement network) at the University of Leeds on 28th November 2018
Disseminating Scientific Papers via Twitter: Practical Insights and Research ...SC CTSI at USC and CHLA
About one-fifth of current scientific papers are being shared on Twitter. With 230 million active users and 24 percent of the U.S. online population using the microblogging platform, hopes are high that tweets mentioning scientific articles reflect some type of interest by the general public and might even be able to measure the societal impact of research. However, early studies show that most of the engagement with scientific papers on Twitter takes place among members of academia and thus reflects visibility within the scientific community rather than impact on society. At the same time, some tweets do not involve any human engagement but rather are generated automatically by Twitter bots.
This talk focuses on identifying audiences on Twitter and teaches participants how to collect, analyze, visualize, and interpret diffusion patterns of scientific articles on Twitter. The course provides an overview of Altmetrics research and present the challenges – including methods and first results – of classifying Twitter user groups, with a particular focus on identifying members of the general public and measuring societal impact. The course will provide hands-on exercises and instructions on how to analyze by whom, when, and how scientific papers are shared on Twitter.
Speaker: Stefanie Haustein, Ph.D., Assistant Professor, School of Information Studies, University of Ottawa
Scholarly Communication: Tools and Strategies for Learning and Sharing in the...Heather Martin
Slides from a discussion I led as part of the Social Science Research Toolkit program (http://blogs.mhsl.uab.edu/sbs/?page_id=85) at Mervyn H. Sterne Library, University of Alabama at Birmingham.
Reputation, impact, and the role of libraries in the world of open scienceKeith Webster
An overview of the relationship between open science, research assessment, university rankings, and the role of librarians in advancing the research university
Science dissemination 2.0: Social media for researchers (MTM-MSc 2022)Xavier Lasauca i Cisa
In this workshop (Master in Translational Medicine-MSc, University of Barcelona's Faculty of Medicine-Hospital Clínic, 25 May 2022) I summarised the benefits which can be gained from use of social media (specially Twitter, blogs and other networks and repositories) to support research activities, and I provided examples of these socialnetwork sites as tools for scientific communication, as well as resources to increase the diffusion, visibility and impact of the scientific production. Structure of the lecture: Introduction,The digital revolution, Altmetrics, Open science, Active listening, Twitter, Professional networking, Blogging, Sharing, Digital identity building, References to deepen and Conclusions.
Ideas that seem obvious today, at one point were obscure facts known only to a select few. The health benefits of washing hands, wearing a seatbelt while in a car - none of these ideas and practices were accepted immediately. In addition to needing time to incubate, new ideas also need to be accessible so that they can be tested, debated, and built upon. This presentation, which is based on my previous research and personal experiences, will highlight the importance and connection between open access publishing and the role of social media in promotion and dissemination of scholarly research.
Similar to Altmetrics: Listening & Giving Voice to Ideas with Social Media Data (20)
Abstract: Ukraine has long been a target for the Kremlin's disinformation campaigns. Since the annexation of Crimea in 2014, Russia has employed a variety of ‘information operation’ tactics to undermine the Ukrainian government and destabilize Ukrainian society. For example, Russia deployed a network of paid internet trolls via the Internet Research Agency to spread disinformation in and about Ukraine. The use of these tactics have only intensified during Russia's invasion of Ukraine in 2022.
The presentation will introduce the ConflictMisinfo.org Dashboard, developed by the Social Media Lab at Toronto Metropolitan University, to monitor online dis- and misinformation about Russia’s invasion of Ukraine. The dashboard captures and visualizes debunked claims from 100s of trusted fact-checkers from around the world. Since the start of the invasion, the dashboard has recorded over 1000 false, misleading and unproven claims related to the Russia-Ukraine war. The second part of the presentation will highlight the results of a new report to be released by the Lab in early July on the Reach of Russian Propaganda and Disinformation in Canada. The presentation will conclude with a number of practical steps to help social media users to detect and limit the spread of dis- and misinformation on this and other topics.
Video presentation at https://www.youtube.com/watch?v=SGTCMzLAbn8
-------------------------------
The goal of this exploratory study was to better understand the online dynamics of violence on Twitter against candidates running for political offices. Online violence on online platforms is a pressing problem. This study will provide research-based evidence for policymakers, governing stakeholders, researchers, and social media intermediaries working to address current knowledge gaps and challenges associated with toxic interactions on platforms like Twitter. It will also help examine the capabilities and overall effectiveness of Twitter’s platform-based guardianship (i.e., automated and human-led content moderation).
Abstract:
On May 25, 2018, the European Union (EU) implemented the General Data Protection Regulation (GDPR) to protect individuals’ privacy and data. This regulation has far-reaching implications as it applies to any organization that deals with data of EU residents. By studying the discussion about this regulation on Twitter, our goal is to examine public opinions and organizational public relations (PR) strategies about GDPR. The results show that the regulation is being actively discussed by a variety of stakeholders, but especially by cybersecurity and IT-related firms and consultants. At the same time, some of the stakeholders that were expected to have a more active role were less involved, including companies that store or process personal data, government and regulatory bodies, mainstream media, and academics. The results also show that the stakeholders mostly have one-way rather than two-way communication with their audiences, thus fulfilling the rhetorical than relational function of PR.
Full paper at http://hdl.handle.net/10125/64061
Molding public opinion is as old as politics. In recent years, as more and more Canadians are spending their time online, the process and methods used to influence public opinions have undergone some major changes. Most recently, these include the emergence of social bots and troll armies designed to shape public discourse. Their impact was felt in 2016 during the U.S. presidential election and the UK Brexit referendum. In both cases, social media platforms have emerged as an important avenue for disinformation operations and misinformation campaigns. Enabled by bots, trolls, and algorithm-driven filter bubbles, the weaponization of social media is undermining and weakening public trust in government institutions across the globe and threatening the future of democracy.
Join us at the next TRSM Dean’s Speaker Series as we dive into the fascinating world of political bots and trolls in Canada with Dr. Anatoliy Gruzd, Director of Research at Ryerson University Social Media Lab at TRSM. Dr. Gruzd will show how his lab uses publicly available social media data to show how misinformation spreads through online social networks on sites like Twitter and Facebook and recent discoveries about how bots and trolls are being injected into the conversation during the 2019 campaign. The event will be moderated by Tom Clark, Chairman, Global Public Affairs.
Bios:
Anatoliy Gruzd, PhD is a Canada Research Chair and Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab in Toronto, Canada. He is also a founding co-editor of a multidisciplinary journal on Big Data and Society. His work explores the inner workings of online communities, studying how people and organizations adapt to social media in various domains, and examining tensions between privacy and self-disclosure on social media networks.
Tom Clark joined Global after almost 45 years at the most senior levels of Canadian journalism. Tom left Global News on January 1, 2017, after serving as the network’s chief political correspondent and host of The West Block. He has interviewed every Canadian Prime Minister since Lester B. Pearson and has covered every federal election campaign since 1974. He has reported in eight active war zones and from over 33 countries. Tom was CTV’s China Bureau Chief and was also its Chief Washington Correspondent for five years. He has a deep understanding of Canada’s position in an increasingly complicated international dynamic. Tom is the recipient of Radio Television Digital News Association lifetime achievement award and has been named one of the most influential journalists in Ottawa.
The talk is given as part of the 2019 Worldviews conference at the panel on "Digital technology’s impact on how media and higher education communicate".
Citation: Kumar, P., & Gruzd, A. (2019). Social Media for Informal Learning: a Case of #Twitterstorians. In Proceedings of HICSS. Retrieved from http://scholarspace.manoa.hawaii.edu/handle/10125/59691
Abstract:
Open, online environments like social media are now a mainstay of life-long informal learning. Social media like Twitter help people gather information, share resources, and discuss with other participant-learners with similar interests. This paper seeks to test and validate the ‘learning in the wild’ coding schema in the context of discussions on Twitter, an approach first developed for studying learning communities on Reddit. The schema considers how participant-learners are leveraging social media to facilitate self-directed informal learning practices, exploratory dialogue, and communicative exchanges. We apply the coding schema on a sample of tweets (n=594) from the History Twittersphere community (#Twitterstorians) to provide a more nuanced understanding of the different kinds of discursive practices, resource exchanges, and ideas being shared and communicated outside traditional classroom settings.
Social media data is a rich source of behavioural data that can reveal how we connect and interact with each other online in real time and over time, and what that might mean for our society as we continue to speed towards an increasingly computer-mediated future. However, much of the data being collected are being used in ways that are not always transparent to the users. Also once collected, the data can be combined with other types of data and analyzed by algorithms to reveal even more sensitive information about the users. As a result, questions around why and how data consumers’ use social media data are becoming pertinent, especially in the aftermath of the Facebook’s Cambridge Analytica scandal. This talk will discuss privacy and ethical implications of working with social media data.
Roundtable at the 2018 AoIR conference.
Anatoliy Gruzd, Jenna Jacobson, Ryerson University, Canada
Jacquelyn Burkell, Western University
Joanne McNeish, Ryerson University
Anabel Quan-Haase, Western University
Abstract
The transnational flows of information across nations and borders make it difficult to introduce and implement privacy-preserving policies relating to social media data. Social media data are a rich source of behavioural data that can reveal how we connect and interact with each other online in real time. Furthermore, the materiality of new digital intermediaries (such as the Internet of Things, AI, and algorithms) raises additional anticipated and unanticipated privacy challenges that need to be addressed as we continue to speed towards an increasingly digitally-mediated future.
A by-product of the large-scale social media adoption is social media data mining; publicly available social media data is largely free and legally available to be mined, analyzed, and used (Kennedy 2016) for whatever purposes by third parties. Researchers have begun to suggest that ethics need to be considered even if the data is public (boyd & Crawford 2012).
In the wake of the EU's recent legislation of the General Data Protection Regulation and the Right to be Forgotten, as well as increasing critical attention around the world, the roundtable will discuss how to navigate the transnational and material, as well as the complex and competing, interests associated with using social media, including ethics, privacy, security, and intellectual property rights. By balancing people's individual rights to exercise autonomy over "their" data and the societal benefits of using and analyzing the data for insights, the roundtable aims to generate theoretically-rich discussion and debate with internet researchers about the ethics, privacy, and best practices of using social media data.
This workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers.
By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.
Instructor’s Bio: Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.
This poster presents a prototype Learning Analytics (LA) dashboard to help educators who use Twitter in their teaching. The system summarizes and visualizes information how online learners contribute to Twitter-based discussions by asking questions, sharing resources, and engaging with others.
Suggested citation:
Gruzd, A. & Conroy, N. (2018). Learning Analytics Dashboard for Twitter. Poster presented at the BayLan Learning Analytics Conference, February 24, 2018, San Francisco, CA, USA.
Abul-Fottouh, D., Song, M. Y., & Gruzd, A. (2020). Examining algorithmic biases in YouTube’s recommendations of vaccine videos. International Journal of Medical Informatics, 104175.
Read our follow-up study at https://doi.org/10.1016/j.ijmedinf.2020.104175
=================================
Song, M.Y. & Gruzd, A. (2017). Examining Sentiments and Popularity of Pro- and Anti-Vaccination Videos on YouTube. In Proceedings of the 8th International Conference on Social Media & Society (#SMSociety17). ACM, New York, NY, USA, Article 17, 8 pages. DOI: https://doi.org/10.1145/3097286.3097303
With the rise of new media and social media, a new era of big data has emerged, which has brought about various methodological and theoretical challenges for conducting social research. With over a billion daily active users, Facebook is widely recognized as the leading social media platform in the world. Beyond the use of Facebook to connect people from around the world, Facebook affords various opportunities for academics to conduct research. In this presentation, we will discuss our approach to integrate Facebook data as part of an online survey to study people’s privacy concerns, with a particular focus on methodological challenges associated with sampling and recruiting participants on Facebook.
Sampling: Considering, there is no easy searchable directory of Facebook Groups or Pages, how do researchers identify and sample Facebook Groups or Pages? Problematically, it is difficult to systematically sample across Facebook to get a “representative” sample of Facebook users. Facebook Group Directory, algorithmically-filtered search, and custom-curated directories can be used to sample; however, each approach introduces biases and challenges.
Recruitment: After the selection of the Group/Page of study, how can researchers invite people to participate in the study? Facebook’s Terms of Service does not allow contacting users directly unless you have conducted “business” with them. We outline the various options for recruitment, including buying an ad, posting directly to the group/page, and contacting the moderator.
Ethics: As more Canadians are joining and contributing to Facebook, their automatically recorded data are rapidly becoming available to third parties to mine for both commercial and academic purposes. Ethical questions need to be considered throughout the entire research process. This is particularly true of social media research, which presents unique ethical and personal considerations. In this part of the presentation, we will outline the Social API Terms of Service online guide created by the Social Media Lab at Ryerson University that Internet researchers can use to learn what they can or cannot do with social media collected from sites like Facebook.
The presentation will conclude with the discussion of our plans to develop a unique Facebook app that will allow any Facebook user to review their publicly available social media data and participate in our survey on Social Media Privacy Concerns.
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.”
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
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.
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.
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/
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.
Altmetrics: Listening & Giving Voice to Ideas with Social Media Data
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. 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. This is what academics
say about Altmetrics on
Twitter
6 years later…
4. This is what academics
say about Altmetrics on
Twitter
6 years later…
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. 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. 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. 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. Who talks about research
on social media?
• Not just academics! But also
• institutions
• journalists
• librarians
• policy makers
• other groups
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. Example: Libraries & Museums
Making Biodiversity Heritage Library (BHL)
collections more “social”!
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. Research on Altmetrics is growing… but still very young
Top 10 most prolific scholars in this area
Source: Web of Science, Sep 2017
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
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%)
25. NISO Alternative Assessment Project
http://www.niso.org/apps/group_public/document.php?document_id=17090
transparency
replicability
accuracy
Altmetrics: Data Aggregators
26. NISO Alternative Assessment Project
http://www.niso.org/apps/group_public/document.php?document_id=17090
Altmetrics:
Data Aggregators
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. 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. Altmetrics: Developing Metrics based on Social Network
Analysis (SNA)
Nodes = Social Media Users
Ties (lines) = Interactions
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. 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. 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)
38. 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
39. 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
40. 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.