Onyx: A Linked Data approach to emotion representation

Sánchez-Rada, J. Fernando; Iglesias, Carlos Á.

doi:10.1016/j.ipm.2015.03.007

Cited by 43 publications

(33 citation statements)

References 15 publications

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“…In addition to the more basic analysis in SA, advanced emotion analysis (AEA) was activated. AEA is a more granular measurement with which to analyse and categorize the texts and to distinguish emotions, such as joy, anger, disgust, sadness, and fear (Sánchez‐Rada & Iglesias ; Thelwall ). In addition, social network analysis via the platform's algorithm made it possible to visualize the complex structure of connections between users.…”

Section: Methodsmentioning

confidence: 99%

Mental health nurses’ use of Twitter for professional purposes during conference participation using #acmhn2016

Salzmann‐Erikson

2017

Int J Mental Health Nurs

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Scholars across different disciplines use Twitter to promote research and to communicate with society. Most conferences nowadays have their unique hashtag in which participants can communicate in real time. Previous research has reported on conference participants' use of Twitter, but no such studies are available in the field of mental health nursing. Thus, the explicit aim of the present study was to examine conference participants' use of Twitter during the 42nd International Mental Health Nursing Conference. Freely-accessible data were mined via a social media platform under the hashtag #acmhn2016. The total dataset consisted of 1973 tweets, and was analysed with descriptive statistics and a directed content analysis. The results demonstrated that 37% of the tweets were original posts, and 63% were engagements. In total, 184 individual accounts engaged in Twitter during the conference, and 16.4 tweets were posted hourly. Most tweets were categorized as conference/session-related content, but Twitter was also used for socializing with other participants. The most frequently-used words mirror a clear connection to a person-centred approach, and deviate from the biomedical terminology. However, not all of the conference participants engaged on Twitter, and might thereby risk being excluded from this backchannel.

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Section: Methodsmentioning

confidence: 99%

Mental health nurses’ use of Twitter for professional purposes during conference participation using #acmhn2016

Salzmann‐Erikson

2017

Int J Mental Health Nurs

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“…For expressing sentiments, we use the Onyx ontology 13 [22]. Through the class onyx:EmotionSet we associate a tweet with a set of emotions (onyx:Emotion).…”

Section: Rdf/s Model For Annotated Tweetsmentioning

confidence: 99%

TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets

Fafalios

Iosifidis

Ntoutsi

et al. 2018

Lecture Notes in Computer Science

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Publicly available social media archives facilitate research in a variety of fields, such as data science, sociology or the digital humanities, where Twitter has emerged as one of the most prominent sources. However, obtaining, archiving and annotating large amounts of tweets is costly. In this paper, we describe TweetsKB, a publicly available corpus of currently more than 1.5 billion tweets, spanning almost 5 years (Jan'13-Nov'17). Metadata information about the tweets as well as extracted entities, hashtags, user mentions and sentiment information are exposed using established RDF/S vocabularies. Next to a description of the extraction and annotation process, we present use cases to illustrate scenarios for entity-centric information exploration, data integration and knowledge discovery facilitated by TweetsKB.

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“…Last, a group of papers focus, on the one hand, on the impact of emotions and sentiment information on different tasks, such as personalized tag-based search (Xie et al, 2015) and author profiling (Rangel & Rosso, 2015), and on the other hand on representing emotions in ontologies, coping with the need for established, shared solutions for the affective analysis of social and expressive media (Sanchez-Rada & Iglesias, 2015).…”

Section: The Essem Special Issuementioning

confidence: 99%

“…The authors integrate the six basic emotions of Ekman (Ekman, 1972) within a novel graph-based approach and propose a model for identifying gender and age in the Spanish partition of the PAN-AP-13 corpus, by achieving comparable results to the best performing systems of the PAN Lab of CLEF 2013 (http://pan.webis.de/). Finally, the work "Onyx: A Linked Data Approach to Emotion Representation" by J. Fernando Sánchez-Rada and Carlos A. Iglesias presents a new semantic vocabulary, called Onyx, to describe in a unified framework emotion analysis processes and results, by using semantic web and linked data technologies in order to connect results from different providers and applications (Sanchez-Rada & Iglesias, 2015). The issue of integrating semantic web representations of lexical resources for sentiment analysis is also addressed.…”

Section: The Essem Special Issuementioning

confidence: 99%