Now showing items 1-8 of 8

  • The colloquial WordNet: Extending Princeton WordNet with neologisms 

    McCrae, John P.; Wood, Ian D.; HIcks, Amanda (Springer International Publishing, 2017-05-27)
    Princeton WordNet is one of the most important resources for natural language processing, but has not been updated for over ten years and is not suitable for analyzing the fast moving language as used on social media. We ...
  • Community topic usage in social networks 

    Wood, Ian D. (ACM, 2015-10)
    When studying large social media data sets, it is useful to reduce the dimensionality of both the network (e.g. by finding communities) and user-generated data such as text (e.g. using topic models). Algorithms exist for ...
  • A comparison of emotion annotation approaches for text 

    Wood, Ian D.; McCrae, John P.; Andryushechkin, Vladimir; Buitelaar, Paul (MDPI, 2018-05-11)
    While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of a more nuanced affect has received less attention: there ...
  • A comparison of emotion annotation schemes and a new annotated data set 

    Wood, Ian D.; McCrae, John P.; Andryushechkin, Vladimir; Buitelaar, Paul (European Languages Resources Association (ELRA), 2018-05-07)
    While the recognition of positive/negative sentiment in text is an established task with many standard data sets and well developed methodologies, the recognition of more nuanced affect has received less attention, and ...
  • First insights on a passive major depressive disorder prediction system with incorporated conversational chatbot 

    Delahunty, Fionn; Wood, Ian D.; Arcan, Mihael (AICS 2018 and CEUR-WS.org, 2018-12-06)
    Almost 50% of cases of major depressive disorder go undiagnosed. In this paper, we propose a passive diagnostic system that combines the areas of clinical psychology, machine learning and conversational dialogue systems. ...
  • MixedEmotions: An open-source toolbox for multi-modal emotion analysis 

    Buitelaar, Paul; Wood, Ian D.; Negi, Sapna; Arcan, Mihael; McCrae, John P.; Abele, Andrejs; Robin, Cécile; Andryushechkin, Vladimir; Ziad, Housam; Sagha, Hesam; Schmitt, Maximilian; Schuller, Björn W.; Sánchez-Rada, J. Fernando; Iglesias, Carlos A.; Navarro, Carlos; Giefer, Andreas; Heise, Nicolaus; Masucci, Vincenzo; Danza, Francesco A.; Caterino, Ciro; Smrž, Pavel; Hradiš, Michal; Povolný, Filip; Klimeš, Marek; Matějka, Pavel; Tummarello, Giovanni (IEEE, 2018-01-25)
    Recently, there is an increasing tendency to embed the functionality of recognizing emotions from the user generated contents, to infer richer profile about the users or contents, that can be used for various automated ...
  • NUIG at EmoInt-2017: BiLSTM and SVR ensemble to detect emotion intensity 

    Andryushechkin, Vladimir; Wood, Ian D.; O'Neill, James (Association for Computational Linguistics, 2017-09-08)
    This paper describes the entry NUIG in the WASSA 20171 shared task on emotion recognition. The NUIG system used an SVR (SVM regression) and BiLSTM ensemble, utilizing primarily n-grams (for SVR features) and tweet word ...
  • Towards a crowd-sourced WordNet for colloquial English 

    McCrae, John P.; Wood, Ian D.; Hicks, Amanda (The Global WordNet Association, 2018-01-08)
    Princeton WordNet is one of the most widely-used resources for natural language processing, but is updated only infrequently and cannot keep up with the fast-changing usage of the English language on social media ...