Source-linked AI summary
Interpreting "altmetrics": viewing acts on social media through the lens of citation and social theories
Stefanie Haustein, Timothy D. Bowman, Rodrigo Costas
TL;DR
The paper addresses the lack of a stable theoretical meaning for heterogeneous altmetrics whose platforms and social norms continually change. It classifies the acts producing online events into access, appraisal, and application, then interprets them through citation and social theories, finding that theoretical fit varies across acts and platforms. The framework is conceptual and requires empirical research to investigate motivations and validate use in evaluation.
Problem
Altmetrics lack a common agreed meaning, while their changing platforms, users, and technical ecosystems complicate interpretation and evaluation.
Method
The paper develops a framework for acts producing online events, classifies them as accessing, appraising, or applying, and interprets them with citation and social theories.
Results
Theories fit the heterogeneous acts unevenly: Mertonian norms fit F1000 reviewing and recommending best, fit blog citations less, and do not fit Twitter mentions well.
Takeaways & Limitations
The framework supports interpreting altmetric events as different kinds of scholarly acts rather than treating heterogeneous metrics as a single construct.
Takeaways & Limitations
The theories cannot fully explain social-media acts, so content analyses and user surveys are needed to investigate motivations and validate their use in research evaluation.
Abstract
from arXiv · showhide
More than 30 years after Cronin's seminal paper on "the need for a theory of citing" (Cronin, 1981), the metrics community is once again in need of a new theory, this time one for so-called "altmetrics". Altmetrics, short for alternative (to citation) metrics -- and as such a misnomer -- refers to a new group of metrics based (largely) on social media events relating to scholarly communication. As current definitions of altmetrics are shaped and limited by active platforms, technical possibilities, and business models of aggregators such as Altmetric.com, ImpactStory, PLOS, and Plum Analytics, and as such constantly changing, this work refrains from defining an umbrella term for these very heterogeneous new metrics. Instead a framework is presented that describes acts leading to (online) events on which the metrics are based. These activities occur in the context of social media, such as discussing on Twitter or saving to Mendeley, as well as downloading and citing. The framework groups various types of acts into three categories -- accessing, appraising, and applying -- and provides examples of actions that lead to visibility and traceability online. To improve the understanding of the acts, which result in online events from which metrics are collected, select citation and social theories are used to interpret the phenomena being measured. Citation theories are used because the new metrics based on these events are supposed to replace or complement citations as indicators of impact. Social theories, on the other hand, are discussed because there is an inherent social aspect to the measurements.
1. Introduction
Altmetrics arise from online scholarly communication events and are intended to complement or replace citation-based indicators. Their interpretation remains unsettled because platforms, users, and technical ecosystems change rapidly.
- Online scholarly activities such as reading, discussing, recommending, downloading, and citing can leave measurable traces earlier or more broadly than citations.
- Altmetrics use traces of scholarly production and use on social media platforms to inform scholarly communication and research evaluation.The movement distinguishes these metrics from traditional citation-based indicators.
- High expectations for broader or earlier impact measurement are tempered because altmetrics are constrained by technological ecosystems and may measure what is technically feasible rather than sensible.
- Organizations increasingly consider these metrics in evaluating scholarly output, creating pressure for scholars to understand and manage their activity in computer-mediated environments.
- Altmetrics lack a settled theoretical meaning because their platforms, user communities, and social norms differ and continue to change.
2. Defining and classifying social media events and metrics
The paper avoids imposing a single definition on heterogeneous altmetrics and instead classifies the acts that produce their online events. Its framework distinguishes research objects, event infrastructures, and increasing levels of engagement across access, appraisal, and application.
- Altmetrics have no common agreed definition beyond capturing different kinds of activity, so the paper classifies underlying acts rather than defining one umbrella metric.
- The framework separates research objects, recorded events, hosts, sources, and consumers, including aggregators and end users.
- The framework distinguishes scholarly documents from agents because the acts and recorded events differ between objects such as articles, researchers, institutions, and funding organizations.
- Acts are grouped into accessing, appraising, and applying, which cover stages and facets of interaction with scholarly documents and agents.
- Engagement generally increases from access through appraisal to application and also increases across act types within each category.For documents, application includes reusing or transforming theories, methods, results, software, or datasets; for agents, it includes collaboration.
- Access includes viewing, downloading, and storing objects; appraisal includes mentions, ratings, discussions, reviews, and citations; application involves substantial reuse or transformation.
3. Introducing potentially relevant theories
The paper uses citation and social theories to interpret the acts that generate online metric events. Citation theories address impact indicators, while social theories address the inherently social character of these measurements.
- Citation and social theories are used to improve understanding of the acts that produce the online events from which metrics are collected.
- Citation theories are relevant because the new metrics are intended to complement or replace citations as indicators of impact.
- Social theories are relevant because the measurements have an inherent social aspect and scholars may face pressure to demonstrate societal impact.
3.1. Citation theories
Citation theory supplies competing lenses for interpreting scholarly references and their social traces, but the paper finds that their fit varies by act and platform. This variation motivates a cautious, theory-informed reading of citation-related metrics.
- Citation theory remains incomplete, creating a parallel need for theories and frameworks that explain social-media-based scholarly communication.
- Twitter mentions may evade recognition when users write scholars’ or papers’ names without platform-specific affordances such as handles or links.
- Normative theory: Normative theory treats citations as indirect indicators of intellectual influence shaped by scientific norms requiring acknowledgment of used work.
- Some citation-theory approaches and network theories remain outside the paper’s treatment and are reserved for future research.
- Social constructivist theory: Social constructivist approaches interpret citations as persuasion and as products of social negotiation rather than solely intellectual debt.
- Social constructivist theory: The Matthew effect describes cumulative recognition in which already-reputed scientists and highly cited publications receive further recognition more readily.
- Concept-symbols theory: The concept-symbols theory treats citations as symbols associating particular ideas, procedures, or data with documents.
3.2. Social theories
The section introduces social theories for interpreting acts that generate online scholarly-metric events. It focuses on social capital, attention economics, and dramaturgical concepts such as self-presentation and impression management.
- Social capital: Social capital treats network connections as reciprocal investments through which actors may gain support, information, or other benefits.The theory distinguishes social capital from economic and cultural capital and links network relationships to possible returns.
- Attention economics: Attention economics frames information seeking as a competition for scarce human attention, making tools that reduce information-sifting costs theoretically significant.Scientists are described as allocating time and effort to maximize attention received while using technologies to locate relevant material efficiently.
- Attention economics: Research on social-media behavior applies attention economics to environments where users contribute information to attract attention and contribute attention while consuming information.The framework has also been used to study novelty and popularity in social networks.
- Dramaturgical framework: The dramaturgical framework explains interaction through self-presentation and impression management, including how people present information about themselves to audiences.These processes are motivated partly by avoiding shame and embarrassment.
- Dramaturgical framework: Studies of Facebook and Twitter show that online content shapes impressions, while users may enhance self-presentations and generate impressions with limited accuracy.Tweet contents and intended recipients influence the conclusions followers draw.
4. Applying theories to selected acts
The paper applies its framework and selected theories to acts involving journal articles, especially saving documents in Mendeley and mentioning them on Twitter. These acts produce interpretable traces but remain constrained by representation, norms, platform dynamics, and technical limits.
- Scope and research objects: The framework focuses on journal articles as research objects while distinguishing scholarly documents from scholarly agents.Other document types and research objects are left for future work, and tracked documents usually require a DOI or comparable identifier.
- Access: Saved in Mendeley: Mendeley readership counts indicate that users added documents to libraries, but adding a document does not necessarily mean it was read.Users may organize documents for citing, professional work, teaching, or self-teaching.
- Access: Saved in Mendeley: Approximately three million Mendeley users are described as mainly students, postdocs, and researchers, but their representativeness of all scientific-document readers is unknown.Possible biases across disciplines, academic age, and countries remain unresolved.
- Access: Saved in Mendeley: Mendeley reader counts correlate with citations at medium to high levels, suggesting that citation theories may help interpret the Mendeley environment.The passage presents this as a similarity between the two metrics rather than as evidence that they are identical.
- Access: Saved in Mendeley: Empirical studies have not established whether users follow norms when saving documents, leaving the influence represented by Mendeley reader counts uncertain.Literature-management norms may differ from citation norms and could develop in the future.
- Access: Saved in Mendeley: Saving to Mendeley can be interpreted as accessing, appraising, or pre-citation activity, including organizing documents, tagging or summarizing them, and preparing to cite.Social-capital and attention-economics perspectives interpret saving as potentially increasing visibility or reducing future information-sifting effort.
- Appraise: Mentioned in a tweet: Twitter mentions require a commonly used identifier or URL because tweets are limited to 140 characters and follow different norms from standardized citations.Highly tweeted papers may reflect ephemeral interests rather than scientific merit.
- Appraise: Mentioned in a tweet: Retweets can amplify a paper’s visibility and produce further retweets, while prestigious journals with large official Twitter audiences obtain especially high tweet counts.The passage links this pattern to platform affordances and promotion through accounts with many followers.
5. Conclusions and Outlook
The chapter offers a conceptual framework for interpreting heterogeneous acts underlying altmetrics and evaluates citation and social theories as explanatory lenses. It finds that theoretical fit varies by act, while platform dynamics, noise, and changing affordances limit interpretation and require further empirical research.
- The framework groups acts underlying altmetrics into accessing, appraising, and applying categories.It is presented as a first conceptual step for understanding online events in scholarly communication.
- Citation theories fit unevenly: Mertonian norms align most with F1000 reviewing and recommending, less with blog citations, and poorly with Twitter mentions.For Mendeley, normative theory mainly applies when saving is linked to later citing.
- The Matthew effect offers the strongest social-constructivist explanation for concentration and skewness across many social media acts.Networked mechanisms such as retweets, follower counts, and Mendeley filtering can increase visibility for documents that already have more events.
- Concept-symbol theory applies most directly to Twitter, where hashtags and related symbols can connect documents with ideas for audiences beyond science.It applies to blog mentions and F1000 reviews to a lesser extent.
- Social capital, attention economics, and impression management provide complementary perspectives on scholars’ platform use and presentation of self.These lenses address networks of resources, reduced time spent finding and attending to information, and public/private identity management.
- Interpretation remains limited by meaningless or erroneous mentions, changing technological affordances, and theories that cannot fully explain heterogeneous acts.Further content analyses and user surveys are needed to investigate motivations and validate research-evaluation uses.