Subtopic Deep Dive
Emojis and Social Attribution Processes
Research Guide
What is Emojis and Social Attribution Processes?
Emojis and Social Attribution Processes examines how emojis shape person perception, trust formation, attribution biases, and cognitive processing in digital interactions.
Experiments reveal emojis influence social judgments in online messaging (Kaye et al., 2017, 199 citations). Neuroimaging and behavioral studies track attribution biases from emoji cues (Maiberger et al., 2023, 42 citations). Over 20 papers since 2014 analyze these effects across platforms.
Why It Matters
Emojis alter trust and relationship formation on platforms like Twitter and messaging apps, impacting social dynamics (Kaye et al., 2017). Facial emojis boost eWOM persuasiveness via emotions-as-social-information theory (Maiberger et al., 2023). Personality traits link to emoji use patterns, affecting phubbing and online venting (Liu & Sun, 2020; Cebollero-Salinas et al., 2022).
Key Research Challenges
Cultural Variability in Emoji Interpretation
Emoji meanings differ across cultures, complicating universal attribution models (Cheng, 2017, 31 citations). Transcultural studies show mismatched emotional intensity regulation in CMC. Attribution biases vary by user background.
Quantifying Attribution Bias Effects
Measuring precise impacts of emojis on trust and perception lacks standardized metrics (Maiberger et al., 2023, 42 citations). Experiments struggle with confounding variables like context. Neuroimaging data shows processing differences but needs replication.
Platform-Specific Social Dynamics
Emoji effects on attribution differ by platform, from blogs to Twitter (Rodríguez-Hidalgo et al., 2017, 43 citations; Tenzer, 2022, 22 citations). Generalizing findings across media remains challenging. Biosignal integration adds complexity (Liu et al., 2019, 53 citations).
Essential Papers
Emojis: Insights, Affordances, and Possibilities for Psychological Science
Linda Kaye, Stephanie A. Malone, Helen J. Wall · 2017 · Trends in Cognitive Sciences · 199 citations
See, Like, Share, Remember: Adolescents’ Responses to Unhealthy-, Healthy- and Non-Food Advertising in Social Media
Gráinne Murphy, Ciara Corcoran, Mimi Tatlow‐Golden et al. · 2020 · International Journal of Environmental Research and Public Health · 143 citations
Media-saturated digital environments seek to influence social media users’ behaviour, including through marketing. The World Health Organization has identified food marketing, including advertising...
Animo
Fannie Liu, Mario Esparza, Maria Pavlovskaia et al. · 2019 · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · 53 citations
We present Animo, a smartwatch app that enables people to share and view each other's biosignals. We designed and engineered Animo to explore new ground for smartwatch-based biosignals social compu...
Expressing emotions in blogs: The role of textual paralinguistic cues in online venting and social sharing posts
Carmina Rodríguez-Hidalgo, Ed S. Tan, Peeter W.J. Verlegh · 2017 · Computers in Human Behavior · 43 citations
Let’s face it: When and how facial emojis increase the persuasiveness of electronic word of mouth
Tobias Maiberger, David W. Schindler, Nicole Koschate‐Fischer · 2023 · Journal of the Academy of Marketing Science · 42 citations
Abstract Facial emojis have increasingly permeated electronic word of mouth (eWOM), but the persuasive consequences of this phenomenon remain unclear. Drawing on emotions as social information (EAS...
¿Digo lo que siento y siento lo que digo? Una aproximación transcultural al uso de los emoticonos y emojis en los mensajes en CMC
Lifen Cheng · 2017 · Fonseca Journal of Communication · 31 citations
The use of emoticons and emojis among online messaging users has achieved a globalized level. This article aims at examining how certain emojis and emoticons are chosen by message senders to regula...
EVOLUTION OF ENGLISH IN THE INTERNET AGE
Abdu Al-Kadi, Rashad Ahmed · 2018 · Indonesian Journal of Applied Linguistics · 28 citations
Although the Internet came into existence in the second half of the twentieth century, its influence on language began to escalate in 1990 onwards. It has drastically changed the way people communi...
Reading Guide
Foundational Papers
Start with Hirose et al. (2014, 12 citations) for emoticon effects on emotional states in text messaging, then Kingsbury (2014) on social anxiety biases.
Recent Advances
Study Maiberger et al. (2023, 42 citations) for EASI theory in eWOM, Liu & Sun (2020, 20 citations) for personality patterns, Cebollero-Salinas et al. (2022) on phubbing.
Core Methods
Experiments manipulate emoji valence for attribution measures; surveys assess personality-usage links; EASI theory frames social inference (Maiberger et al., 2023; Liu & Sun, 2020).
How PapersFlow Helps You Research Emojis and Social Attribution Processes
Discover & Search
Research Agent uses searchPapers and exaSearch to find Kaye et al. (2017) on emoji affordances, then citationGraph reveals Maiberger et al. (2023) and Liu & Sun (2020) as high-impact descendants. findSimilarPapers expands to cultural studies like Cheng (2017).
Analyze & Verify
Analysis Agent applies readPaperContent to extract EASI theory from Maiberger et al. (2023), verifies claims with CoVe against Kaye et al. (2017), and runs PythonAnalysis on citation data for bias trends using pandas. GRADE scores evidence strength for neuroimaging claims.
Synthesize & Write
Synthesis Agent detects gaps in transcultural replication post-Cheng (2017), flags contradictions between platforms. Writing Agent uses latexEditText, latexSyncCitations for Kaye (2017) and Maiberger (2023), latexCompile for reports, exportMermaid for attribution bias flowcharts.
Use Cases
"Analyze personality traits linked to emoji usage patterns from Liu & Sun (2020)"
Research Agent → searchPapers('Liu Sun emojis personality') → Analysis Agent → runPythonAnalysis(pandas correlation on usage data) → statistical output with p-values and visualizations.
"Draft LaTeX review on emoji effects in eWOM per Maiberger et al. (2023)"
Synthesis Agent → gap detection → Writing Agent → latexEditText(structure review) → latexSyncCitations(Kaye 2017, Maiberger 2023) → latexCompile → PDF with integrated citations.
"Find code for biosignal emoji analysis like Animo app"
Research Agent → paperExtractUrls(Liu et al. 2019) → Code Discovery → paperFindGithubRepo → githubRepoInspect → wearable biosignal processing scripts.
Automated Workflows
Deep Research workflow scans 50+ papers via searchPapers on 'emojis attribution bias', chains citationGraph to foundational Hirose (2014), outputs structured report with GRADE scores. DeepScan applies 7-step CoVe to verify cultural claims in Cheng (2017) against Kaye (2017). Theorizer generates hypotheses on emoji-trust models from Maiberger (2023) and Liu & Sun (2020).
Frequently Asked Questions
What defines Emojis and Social Attribution Processes?
It studies how emojis influence person perception, trust, biases, and cognitive processing in digital communication (Kaye et al., 2017).
What methods are used?
Behavioral experiments test perception biases; neuroimaging examines processing; surveys link personality to usage (Maiberger et al., 2023; Liu & Sun, 2020).
What are key papers?
Kaye et al. (2017, 199 citations) on affordances; Maiberger et al. (2023, 42 citations) on eWOM; Hirose et al. (2014) foundational on emotional states.
What open problems exist?
Transcultural standardization, platform generalization, and biosignal integration lack resolution (Cheng, 2017; Liu et al., 2019).
Research Digital Communication and Language with AI
PapersFlow provides specialized AI tools for Computer Science researchers. Here are the most relevant for this topic:
AI Literature Review
Automate paper discovery and synthesis across 474M+ papers
Code & Data Discovery
Find datasets, code repositories, and computational tools
Deep Research Reports
Multi-source evidence synthesis with counter-evidence
AI Academic Writing
Write research papers with AI assistance and LaTeX support
See how researchers in Computer Science & AI use PapersFlow
Field-specific workflows, example queries, and use cases.
Start Researching Emojis and Social Attribution Processes with AI
Search 474M+ papers, run AI-powered literature reviews, and write with integrated citations — all in one workspace.
See how PapersFlow works for Computer Science researchers