Relevance of Emoticons in Computer-Mediated Communication Contexts: An Overview
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the constant growth in Information and Communication Technology (ICT) in the last 50 years or so, electronic communication has become part of the present day system of living. Equally, smileys or emoticons were innovated in 1982, and today the genre has attained a substantial patronage in various aspects of computer-mediated communication (CMC). Ever since written forms of electronic communication lack the face-to-face (F2F) situation attributes, emoticons are seen as socio-emotional suppliers to the CMC. This article reviews scholarly research in that field in order to compile variety of investigations on the application of emoticons in some facets of CMC, i.e. Facebook, Instant Messaging (IM), and Short Messaging Service (SMS). Key findings of the review show that emoticons do not just serve as paralanguage elements rather they are compared to word morphemes with distinctive significative functions. In other words, they are morpheme-like units and could be derivational, inflectional, or abbreviations but not unbound. The findings also indicate that emoticons could be conventionalized as well as being paralinguistic elements, therefore, they should be approached as contributory to conversation itself not mere compensatory to language.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it