Emojis as Contextual Indicants in Location-Based Social Media Posts

Hauthal, Eva; Dunkel, Alexander; Burghardt, Dirk

doi:10.3390/ijgi10060407

Cited by 8 publications

(10 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Typicality is derived from the adjective typical which describes the “state of being that is typical”. The formula was developed to combine two relative frequencies: one of a sub-dataset and the other of a total dataset (including the sub-dataset) of emojis or something similar (Hauthal et al 2021 ). The typicality t is described by (Eq.…”

Section: Methodsmentioning

confidence: 99%

Analyzing the EU Migration Crisis as Reflected on Twitter

Mukherjee

Hauthal

Burghardt

2022

KN J. Cartogr. Geogr. Inf.

Self Cite

View full text Add to dashboard Cite

The proliferation of social media has resulted in its extensive use as a valuable source of information for researchers. This paper aims to use Twitter data to analyze and visualize tweets about the migration crisis in the European Union from 2016 to 2021. The paper uses a methodology to structure data for better understanding of complex social media data. The methods and metrics include the facet model of location based social media, the HyperLogLog data structure and novel uses of the metric typicality. The authors have also developed a web based interactive application closely following the methodology used to organize the dataset. Additionally the work also includes maps using spatial typicality which could be utilized for studying spatial phenomenon. The case study selected also provides unique insights and sets a template for working with multi-lingual geo-social media data. The authors believe that these methods and metrics could be reproduced for other case studies and aid in understanding and communication geo-social media data.

show abstract

Section: Methodsmentioning

confidence: 99%

Analyzing the EU Migration Crisis as Reflected on Twitter

Mukherjee

Hauthal

Burghardt

2022

KN J. Cartogr. Geogr. Inf.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Their use in geosocial media is just as popular as the use of hashtags (Bai et al 2019;Highfield and Leaver 2016), and as a language-independent characters, they have the advantage of avoiding error-prone language processing (Hu et al 2013;Kralj Novak et al 2015). The use of emojis is influenced by regional and cultural context (Kejriwal et al 2021), so emojis have great potential to characterize spatial context but also analyze activities related to places and events (Hauthal et al 2021).…”

Section: Related Workmentioning

confidence: 99%

Volunteered Geographic Information

Yuan¹,

Chung²

2022

Encyclopedia of Tourism Management and Marketing

View full text Add to dashboard Cite

use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

show abstract

“…In order to analyze the data more deeply, emoji usage must be normalized. The typicality measure, first introduced by Hauthal et al (2021), allows for the calculation of normalized differences of relative frequencies, in this case effectively identifying the most characteristic emojis within a designated subset of a larger dataset.…”

mentioning

confidence: 99%