• DocumentCode
    2964135
  • Title

    We Have No Feelings, We Have Emoticons ;-)

  • Author

    Rojas, Sarah Leon ; Kirschenmann, Uwe ; Wolpers, Martin

  • fYear
    2012
  • fDate
    4-6 July 2012
  • Firstpage
    642
  • Lastpage
    646
  • Abstract
    Positive emotions have been proven to be a key factor for successful learning. In modern personalized learning environments informal learning takes a prominent role and with this the use of computer-mediated communication. Communication data, like for example chat logs, can be harvested for sentiments. Most sentiment analyses operate processing only verbal information. But the messages exchanged in text based chat also contain low key nonverbal communication. Emoticons are used to compensate the missing visual information and communicate emotions. In this paper we want to introduce a method to perform a sentiment analysis on text based chat logs relying only on emoticons to detect positive sentiment. We implemented and tested this method for the instant messenger Skype. Our first results show emoticons do indeed represent a strong indicator for detecting positivity within chat communication.
  • Keywords
    cognition; computer aided instruction; computer mediated communication; data mining; electronic messaging; emotion recognition; social networking (online); text analysis; Skype; chat communication; computer-mediated communication; emoticons; informal learning; instant messenger; message exchange; missing visual information compensation; nonverbal communication; personalized learning environment; positive sentiment detection; sentiment analyses; text based chat; text based chat log; verbal information processing; Computers; Context; Data mining; Databases; Face; Privacy; Visualization; computer aided analysis; data analysis; data mining; instant messaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Learning Technologies (ICALT), 2012 IEEE 12th International Conference on
  • Conference_Location
    Rome
  • Print_ISBN
    978-1-4673-1642-2
  • Type

    conf

  • DOI
    10.1109/ICALT.2012.180
  • Filename
    6268198