Literature DB >> 28364283

Lisbon Emoji and Emoticon Database (LEED): Norms for emoji and emoticons in seven evaluative dimensions.

David Rodrigues1,2, Marília Prada3, Rui Gaspar4, Margarida V Garrido3, Diniz Lopes3.   

Abstract

The use of emoticons and emoji is increasingly popular across a variety of new platforms of online communication. They have also become popular as stimulus materials in scientific research. However, the assumption that emoji/emoticon users' interpretations always correspond to the developers'/researchers' intended meanings might be misleading. This article presents subjective norms of emoji and emoticons provided by everyday users. The Lisbon Emoji and Emoticon Database (LEED) comprises 238 stimuli: 85 emoticons and 153 emoji (collected from iOS, Android, Facebook, and Emojipedia). The sample included 505 Portuguese participants recruited online. Each participant evaluated a random subset of 20 stimuli for seven dimensions: aesthetic appeal, familiarity, visual complexity, concreteness, valence, arousal, and meaningfulness. Participants were additionally asked to attribute a meaning to each stimulus. The norms obtained include quantitative descriptive results (means, standard deviations, and confidence intervals) and a meaning analysis for each stimulus. We also examined the correlations between the dimensions and tested for differences between emoticons and emoji, as well as between the two major operating systems-Android and iOS. The LEED constitutes a readily available normative database (available at www.osf.io/nua4x ) with potential applications to different research domains.

Entities:  

Keywords:  Aesthetic appeal; Android; Arousal; Concreteness; Emoji; Emoticons; Facebook; Familiarity; ICTs; LEED; Meaning analysis; Meaningfulness; Normative ratings; Valence; Visual complexity; iOS

Mesh:

Year:  2018        PMID: 28364283     DOI: 10.3758/s13428-017-0878-6

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  17 in total

1.  RealPic: Picture norms of real-world common items.

Authors:  Cristiane Souza; Margarida V Garrido; Magda Saraiva; Joana C Carmo
Journal:  Behav Res Methods       Date:  2021-02-10

2.  The taste & affect music database: Subjective rating norms for a new set of musical stimuli.

Authors:  David Guedes; Marília Prada; Margarida Vaz Garrido; Elsa Lamy
Journal:  Behav Res Methods       Date:  2022-05-17

3.  Emoji-SP, the Spanish emoji database: Visual complexity, familiarity, frequency of use, clarity, and emotional valence and arousal norms for 1031 emojis.

Authors:  Pilar Ferré; Juan Haro; Miguel Ángel Pérez-Sánchez; Irene Moreno; José Antonio Hinojosa
Journal:  Behav Res Methods       Date:  2022-06-17

4.  Nudge and bias in subjective ratings? The role of icon sets in determining ratings of icon characteristics.

Authors:  Siné McDougall; Irene Reppa; Jacqui Taylor
Journal:  Behav Res Methods       Date:  2022-10-11

5.  Diabetes on Twitter: A Sentiment Analysis.

Authors:  Elia Gabarron; Enrique Dorronzoro; Octavio Rivera-Romero; Rolf Wynn
Journal:  J Diabetes Sci Technol       Date:  2018-11-19

6.  KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces.

Authors:  Margarida V Garrido; Marília Prada
Journal:  Front Psychol       Date:  2017-12-19

7.  Subjective ratings and emotional recognition of children's facial expressions from the CAFE set.

Authors:  Marília Prada; Margarida V Garrido; Cláudia Camilo; David L Rodrigues
Journal:  PLoS One       Date:  2018-12-27       Impact factor: 3.240

8.  Animal Images Database: Validation of 120 Images for Human-Animal Studies.

Authors:  Catarina Possidónio; João Graça; Jared Piazza; Marília Prada
Journal:  Animals (Basel)       Date:  2019-07-24       Impact factor: 2.752

9.  A Systematic Review of Emoji: Current Research and Future Perspectives.

Authors:  Qiyu Bai; Qi Dan; Zhe Mu; Maokun Yang
Journal:  Front Psychol       Date:  2019-10-15

10.  Can an Emoji a Day Keep the Doctor Away? An Explorative Mixed-Methods Feasibility Study to Develop a Self-Help App for Youth With Mental Health Problems.

Authors:  Levi Van Dam; Sianne Rietstra; Eva Van der Drift; Geert Jan J M Stams; Rob Van der Mei; Maria Mahfoud; Arne Popma; Eric Schlossberg; Alex Pentland; Todd G Reid
Journal:  Front Psychiatry       Date:  2019-08-23       Impact factor: 4.157

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