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@misc{kokkinakis-etal-2022-proceedings-317658,
	title        = {Proceedings of LREC 2022 Workshop: Resources and ProcessIng of linguistic, para-linguistic and extra-linguistic Data from people with various forms of cognitive/psychiatric/developmental impairments.  (RaPID-2012), Saturday 25th of June 2022.
},
	abstract     = {RaPID-4 aims to be an interdisciplinary forum for researchers to share information, findings, methods, models and experience on the collection and processing of data produced by people with various forms of mental, cognitive, neuropsychiatric, or neurodegenerative impairments, such as aphasia, dementia, autism, bipolar disorder, Parkinson's disease or schizophrenia. Particularly, the workshop's focus is on creation, processing and application of data resources from individuals at various stages of these impairments and with varying degrees of severity. Creation of resources includes e.g. the annotation, description, analysis and interpretation of linguistic, paralinguistic and extra-linguistic aspects of such data (i.e. spontaneous spoken language, transcripts, eye tracking, wearable and sensor measurements, digital biomarkers, etc.). Processing of such data can be used to identify, extract, correlate, evaluate and disseminate various linguistic or multimodal phenotypes and measurements, which then can be applied to aid diagnosis, monitor the progression or predict individuals at risk.
A central aim is to facilitate the study of the relationships among various levels of linguistic, paralinguistic and extra-linguistic observations (e.g., acoustic measures; phonological, syntactic and semantic features; eye tracking, sensors, signs and multimodal signals). Submission of papers are invited in all of the aforementioned areas, particularly emphasizing multidisciplinary aspects of processing such data and the interplay between clinical/nursing/medical sciences, language technology, computational linguistics, natural language processing (NLP) and computer science. The workshop will act as a stimulus for the discussion of several ongoing research questions driving current and future research by bringing together researchers from various research communities.  },
	author       = {Kokkinakis, Dimitrios and Themistocleous, Charalambos K. and Lundholm Fors, Kristina and Tsanas, Athanasios and Fraser, Kathleen C.},
	year         = {2022},
	publisher    = {European Language Resources Association},
	address      = {Paris},
	ISBN         = {979-10-95546-77-1},
}

@inProceedings{kokkinakis-etal-2022-necessity-321865,
	title        = {The necessity of digital health communication in social media to boost COVID-19 vaccine acceptance.
},
	booktitle    = {ICA Post Conference: Digital Health Communication: Issues and Perspectives. University of Burgundy Franche-Comté, Dijon, France.},
	author       = {Kokkinakis, Dimitrios and Hammarlin, Mia-Marie and Borin, Lars and Miegel, Fredrik},
	year         = {2022},
}

@inProceedings{kokkinakis-hammarlin-2022-negative-321864,
	title        = {Negative vaccine voices in Swedish social media
},
	abstract     = {Vaccinations are one of the most significant interventions to public health, but vaccine
hesitancy creates concerns for a portion of the population in many countries, including
Sweden. Since discussions on vaccine hesitancy are often taken on social networking
sites, data from Swedish social media are used to study and quantify the sentiment
among the discussants on the vaccination-or-not topic during phases of the COVID-19
pandemic. Out of all the posts analyzed a majority showed a stronger negative
sentiment, prevailing throughout the whole of the examined period, with some spikes
or jumps due to the occurrence of certain vaccine-related events distinguishable in the
results. Sentiment analysis can be a valuable tool to track public opinions regarding the
use, efficacy, safety, and importance of vaccination.
},
	booktitle    = {Proceedings of the 13th International Conference of Experimental Linguistics},
	author       = {Kokkinakis, Dimitrios and Hammarlin, Mia-Marie},
	year         = {2022},
}