Articole din publicaţii internaţionale: Recent submissions

  • Sentiments and Opinions Annotation in User-generated Texts 
    BOBICEV, Victoria (Institutul de Matematică şi Informatică al AŞM, 2011)
    In this work, we analyze sentiments and opinions expressed in user-written Web messages. The messages discuss health related topics: medications, treatment, illness and cure, etc. Recognition of sentiments and opinions is ...
  • Sentiment and Factual Transitions in Online Medical Forums 
    BOBICEV, Victoria; SOKOLOVA, Marina; OAKES, Michael (Springer Nature Switzerland, 2015)
    This work studies sentiment and factual transitions on an online medical forum where users correspond in English. We work with discussions dedicated to reproductive technologies, an emotionally-charged issue. In several ...
  • Sentiment analysis in the Ukrainian and Russian news 
    BOBICHEV, Victoria; KANISHCHEVA, Olga; CHEREDNICHENKO, Olga (IEEE, 2017)
    In this article, we explore the task of sentiment analysis for Ukrainian and Russian news, analyze different approaches and linguistics resources for sentiment analysis. We developed a corpus of Ukrainian and Russian news ...
  • Romanian associative dictionary 
    BOBICEV, Victoria; MAXIM, Victoria (Faculty of Computer Science "Alexandru Ioan Cuza" University of Iași, 2012)
    The paper reports about an experiment of creation and development of an associative dictionary for the Romanian language. It outlines the first phase of the experiment when word associations were collected using questionnaire ...
  • Recognition of Sentiment Sequences in Online Discussions 
    BOBICEV, Victoria; SOKOLOVA, Marina; OAKES, Michael (Association for Computational Linguistics and Dublin City University, 2014)
    Currently 19%-28% of Internet users participate in online health discussions. In this work, we study sentiments expressed on online medical forums. As well as considering the predominant sentiments expressed in individual ...
  • Particularităţi specifice folclorului din Republica Moldova comparativ cu cel din România. Studiu pe un corpus adnotat sub formă de arbori sintactici 
    MĂRĂNDUC, Cătălina; BOBICEV, Victoria (Editura Academiei Române, 2019)
    We have created a subcorpus of the treebank in dependency grammar of the Faculty of Computer Science, Al. I. Cuza University, containing folklore collected from the Republic of Moldova, annotated there by the students of ...
  • Parsing temporal and spatial information 
    MĂRĂNDUC, Cătălina; BOBICEV, Victoria; PEREZ, Cenel Augusto (Romanian Academy, Bucharest, 2020)
    In this paper we present a dependency treebank morphologically and syntactically annotated in a specific scheme. We managed to increase the accuracy of the POS-tagger and the syntactic parser used, which led to the increase ...
  • Parsing Romanian Texts 
    MǍRǍNDUC, Cǎtǎlina; BOBICEV, Victoria; UNTILOV, Roman (IEEE, 2020)
    The paper describes the experiments of automatic parsing on a Romanian corpus that contains various types of Romanian texts. The corpus has morphological and syntactic annotations using the dependency grammar model. We ...
  • No Sentiment is an Island 
    BOBICEV, Victoria; SOKOLOVA, Marina (Springer Nature Switzerland, 2015)
    In this study we propose a new method to classify sentiments in messages posted on online forums. Traditionally, sentiment classification relies on analysis of emotionally-charged words and discourse units found in the ...
  • Native Language Identification with PPM 
    BOBICEV, Victoria (Association for Computational Linguistics, 2013)
    This paper reports on our work in the NLI shared task 2013 on Native Language Identification. The task is to automatically detect the native language of the TOEFL essays authors in a set of given test documents in English. ...
  • Learning Sentiments from Tweets with Personal Health Information 
    BOBICEV, Victoria; SOKOLOVA, Marina; JAFER, Yasser; SCHRAMM, David (Springer Nature Switzerland, 2012)
    We present results of sentiment analysis in Twitter messages that disclose personal health information. In these messages (tweets), users discuss ailment, treatment, medications, etc. We use the author-centric annotation ...
  • Learning Relationship between Authorsʹ Activity and Sentiments: A case study of online medical forums 
    SOKOLOVA, Marina; BOBICEV, Victoria (INCOMA Ltd., 2015)
    Our current work analyses relations between sentiments and activity of authors of online In-Vitro Fertilization forums. We focus on two types of active authors: those who start new discussions and those who post significantly ...
  • Inter-Annotator Agreement in Sentiment Analysis: Machine Learning Perspective 
    BOBICEV, Victoria; SOKOLOVA, Marina (INCOMA Ltd., 2017)
    Manual text annotation is an essential part of Big Text analytics. Although annotators work with limited parts of data sets, their results are extrapolated by automated text classification and affect the final classification ...
  • Good News vs. Bad News: What are they talking about? 
    KANISHCHEVA, Olga; BOBICEV, Victoria (INCOMA Ltd., 2017)
    Today’s massive news streams demand the automate analysis which is provided by various online news explorers. However, most of them do not provide sentiment analysis. The main problem of sentiment analysis of news is the ...
  • Confused and Thankful: Multi-label Sentiment Classification of Health Forums 
    BOBICEV, Victoria; SOKOL, Marina (Springer Nature Switzerland, 2017)
    Our current work studies sentiment representation in messages posted on health forums. We analyze 11 sentiment representations in a framework of multi-label learning. We use Exact Match and F-score to compare effectiveness ...
  • Comparison of Word-based and Letter-based Text Classification 
    BOBICEV, Victoria (Association for Computational Linguistics, 2007)
    In this paper the comparison of two PPM (Prediction by Partial Matching) methods for automatic content-based text classification is described: on the basis of letters and on the basis of words. The investigation was driven ...
  • Classification of Emotion Words in Russian and Romanian Languages 
    SOKOLOVA, Marina; BOBICEV, Victoria (Association for Computational Linguistics, 2009)
    This paper presents a machine learning study of affective words in Russian and Romanian languages. We tag the word affective meaning by one of the WordNet Affect six labels anger, disgust, fear, joy, sadness, surprise and ...
  • Can Anonymous Posters on Medical Forums be Reidentified? 
    BOBICEV, Victoria; SOKOLOVA, Marina; EL EMAM, Khaled; JAFER, Yasser; DEWAR, Brian; JONKER, Elizabeth; MATWIN, Stan (JMIR Publications, 2013)
    The goal was to build a system that accurately attributes authorship of messages posted on medical forums. The Authorship Attributor system uses text analysis techniques to crawl medical forums and automatically correlate ...
  • Automatic Detection of Arabicized Berber and Arabic Varieties 
    ADOUANE, Wafia; SEMMAR, Nasredine; JOHANSSON, Richard; BOBICEV, Victoria (The COLING 2016 Organizing Committee, 2016)
    Automatic Language Identification (ALI) is the detection of the natural language of an input text by a machine. It is the first necessary step to do any language-dependent natural language processing task. Various methods ...
  • Authorship Detection with PPM 
    BOBICEV, Victoria (CEUR, 2013)
    This paper reports on our work in the PAN 2013 author identification task. The task is to automatically detect the author of the given text having small training sets with known authors. The task was solved by a system ...

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