Updated on 2022/05/26

写真a

 
OHMAN, Emily
 
Affiliation
Faculty of International Research and Education, School of International Liberal Studies
Job title
Assistant Professor(tenure-track)

Education

  • 2016.01
    -
    2021.03

    University of Helsinki   Department of Digital Humanities - Language Technology   PhD  

    "The Language of Emotions: Building and Applying Resources for Computational Approaches to Emotion Detection for English and Beyond"

  • 2016
    -
    2021

    University of Helsinki   HYPE (Centre for University Teaching and Learning)   30 credits of University pedagogy  

  • 2016.07
     
     

    Instituto Superior Técnico (IST)   Lisbon Machine Learning Summer School  

  •  
    -
    2015.10

    Linnaeus University   Department of English   MA in English Linguistics  

Research Experience

  • 2021.04
    -
    Now

    Waseda University   School of International Liberal Studies   Assistant Professor

    Digital Humanities research base creation

  • 2020.12
    -
    2021.03

    Tampere University   Faculty of Information Technology and Communication Sciences   Intimacy in Data-driven Culture   Postdoc

  • 2020.09
    -
    2021.03

    University of Helsinki / Tampere University / Consumer Society Research Centre   Unconventional Communicators in the Corona Crisis (UnCoCo)   Postdoc

    Group grant

  • 2016.01
    -
    2021.03

    University of Helsinki   Department of Digital Humanities   PhD project in Language Technology   Doctoral Student

  • 2014.09
    -
    2015.12

    University of Helsinki   Department of English   Language Change Database   Research Assistant

  • 2004
    -
    2005

    Gothenburg University   Department of Linguistics   European Intercultural Workplace: Sweden

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Professional Memberships

  • 2021
    -
    Now

    Japanese Association for Digital Humanities

  • 2020
    -
    Now

    European Association for Digital Humanities

  • 2018
    -
    Now

    Rajapinta ry (Computational Social Science)

  • 2018
    -
    Now

    Digital Humanities in the Nordic Countries

 

Research Areas

  • Linguistics

  • Computational science

  • Science education

  • Tertiary education

  • Library and information science, humanistic and social informatics

Research Interests

  • digital humanities, computational linguistics, language technology, computational social science, computational literary studies, NLP, sentiment analysis, emotion detection, machine learning, social media analysis, affect studies

Papers

  • XED: A Multilingual Dataset for Sentiment Analysis and Emotion Detection.

    Emily Öhman, Marc Pàmies, Kaisla Kajava, Jörg Tiedemann

    Proceedings of the 28th International Conference on Computational Linguistics(COLING)     6542 - 6552  2020  [Refereed]

    Authorship:Lead author, Corresponding author

    DOI

  • Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation.

    Emily Öhman, Kaisla Kajava, Jörg Tiedemann, Timo Honkela

    Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis(WASSA@EMNLP)     24 - 30  2018  [Refereed]

    Authorship:Lead author, Corresponding author

    DOI

  • From hate speech recognition to happiness indexing: critical issues in datafication of emotion in text mining

    Laaksonen, S-M, Paakonen, J, Ohman,E

    Handbook of Critical Studies of Artificial Intelligence    2023  [Refereed]

    Authorship:Lead author

  • Strategic sentiments and emotions in post-Second World War party manifestos in Finland

    Koljonen, J, Ohman, E, Ahonen, P, Mattila, M

    Journal of Computational Social Science    2022  [Refereed]

  • Hate speech, Censorship, and Freedom of Speech: The Changing Policies of Reddit

    Elissa Nakajima Wickham, Emily Ohman

    Journal of Data Mining and Digital Humanities    2022  [Refereed]

    Authorship:Corresponding author

  • SELF & FEIL: Emotion Lexicons for Finnish

    Öhman Emily

    Proceedings of the 6th Digital Humanities in the Nordic and Baltic Countries Conference (DHNB 2022), Uppsala, Sweden, March 15-18, 2022.    2022  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    This paper introduces a Sentiment and Emotion Lexicon for Finnish (SELF) and a Finnish Emotion Intensity Lexicon (FEIL). We describe the lexicon creation process and evaluate the lexicon using some commonly available tools. The lexicon uses annotations projected from the NRC Emotion Lexicon with carefully edited translations. To our knowledge, this is the first comprehensive sentiment and emotion lexicon for Finnish.

  • Japanese Beauty Marketing on Social Media: Critical Discourse Analysis Meets NLP

    Emily Ohman, Amy Grace Metcalfe

    Proceedings of Natural Language Processing for Digital Humanities @ ICON 2021    2021.12  [Refereed]

    Authorship:Lead author, Corresponding author

  • The Validity of Lexicon-based Sentiment Analysis in Interdisciplinary Research

    Emily Ohman

    Proceedings of Natural Language Processing for Digital Humanities @ ICON 2021    2021.12  [Refereed]

    Authorship:Lead author, Corresponding author

  • The Language of Emotions

    Öhman Emily

       2021.03  [Refereed]  [International journal]

    Authorship:Lead author, Corresponding author

     View Summary

    Emotions have always been central to the human experience: the ancient Greeks had philosophical debates about the nature of emotions and Charles Darwin can be said to have founded the modern theories of emotions with his study The expression of the emotions in man and animals. Theories of emotion are still actively researched in many different fields from psychology, cognitive science, and anthropology to computer science.

    Sentiment analysis usually refers to the use of computational tools to identify and extract sentiments and emotions from various modalities. In this dissertation, I use sentiment analysis in conjunction with natural language processing to identify, quantify, and classify emotions in text. Specifically, emotions are examined in multilingual settings using multidimensional models of emotions.

    Plutchik’s wheel of emotions and emotional intensities are used to classify emotions in parallel corpora via both lexical methods and supervised machine learning methods. By analyzing emotional language content in text, the connection between language and emotions can be better understood. I have developed new approaches to create a more equitable natural language processing approach for sentiment analysis, meaning the development and evaluation of massively multilingual annotated datasets, contributing to the provision of tools for under-resourced languages.

    This dissertation is comprised of ten articles on related topics in sentiment analysis. In these articles, I discuss lexicon-based methods and the creation of emotion and sentiment lexicons, the creation of datasets for supervised machine learning, the training of models for supervised machine learning, and the evaluation of such models. I also examine the annotation process in relation to creating datasets in-depth, including the creation of
    a lightweight easily deployed annotation platform. As an additional step, I test the different approaches in downstream applications.

    These practical applications include the study of political party rhetoric from the perspective of emotion words used and the intensities of those emotion words. I also examine how simple lexicon-based methods can be used to make the study of affect in literature less subjective. Additionally, I attempt to link sentiment analysis with hate speech detection and offensive speech target identification.

    The main contribution of this dissertation is in providing tools for sentiment analysis and in demonstrating how these tools can be augmented for use in a wide variety of languages and practical applications at low cost.

  • Emotion annotation: Rethinking emotion categorization

    Emily Öhman

    CEUR Workshop Proceedings   2865   134 - 144  2020  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    One of the biggest hurdles for the utilization of machine learning in interdisciplinary projects is the need for annotated training data which is costly to create. Emotion annotation is a notoriously difficult task, and the current annotation schemes which are based on psychological theories of human interaction are not always the most conducive for the creation of reliable emotion annotations, nor are they optimal for annotating emotions in the modality of text. This paper discusses the theory, history, and challenges of emotion annotation, and proposes improvements for emotion annotation tasks based on both theory and case studies. These improvements focus on rethinking the categorization of emotions and the overlap and disjointedness of emotion categories.

  • LT@Helsinki at SemEval-2020 Task 12: Multilingual or Language-specific BERT?

    Marc Pàmies, Emily Öhman, Kaisla Kajava, Jörg Tiedemann

    Proceedings of the Fourteenth Workshop on Semantic Evaluation(SemEval@COLING)     1569 - 1575  2020  [Refereed]

    Authorship:Corresponding author

  • Challenges in annotation: Annotator experiences from a crowdsourced emotion annotation task

    Emily Öhman

    CEUR Workshop Proceedings   2612   293 - 301  2020  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    With the prevalence of machine learning in natural language processing and other fields, an increasing number of crowd-sourced data sets are created and published. However, very little has been written about the annotation process from the point of view of the annotators. This pilot study aims to help fill the gap and provide insights into how to maximize the quality of the annotation output of crowd-sourced annotations with a focus on fine-grained sentence-level sentiment and emotion annotation from the annotators point of view.

  • Emotion preservation in translation: Evaluating datasets for annotation projection

    Kaisla Kajava, Emily Öhman, Piao Hui, Jörg Tiedemann

    CEUR Workshop Proceedings   2612   38 - 50  2020  [Refereed]

    Authorship:Corresponding author

     View Summary

    This paper is a pilot study that aims to explore the viability of annotation projection from one language to another as well as to evaluate the multilingual data set we have created for emotion analysis. We study different language pairs based on parallel corpora for sentiment and emotion annotations and explore annotator agreement. We show that the data source is a possible one for reliable L1 data to be used in annotation projection from high-resource languages, such as English, into low-resource languages and that this is a reliable way of creating data sets for fine-grained sentiment analysis and emotion detection.

  • Teaching computational methods to humanities students

    Emily Öhman

    CEUR Workshop Proceedings   2364   479 - 493  2019  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    This paper discusses the academic and societal implications of teaching computational methods to humanities students from the perspective of digital humanities. Pedagogical choices are backed up by both pedagogical theory and concrete examples from actual courses and course feedback. The aim of this paper is to introduce clear best-practice recommendations for developing digital humanities teaching with an emphasis on methods teaching in order to increase the number of students who understand such methods and can apply them to their own projects.

  • Sentimentator: Gamifying fine-grained sentiment annotation

    Emily Öhman, Kaisla Kajava

    CEUR Workshop Proceedings   2084   98 - 110  2018  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    We introduce Sentimentator; a publicly available gamified web-based annotation platform for fine-grained sentiment annotation at the sentence-level. Sentimentator is unique in that it moves beyond binary classification. We use a tendimensional model which allows for the annotation of 51 unique sentiments and emotions. The platform is gamified with a complex scoring system designed to reward users for high quality annotations. Sentimentator introduces several unique features that have previously not been available, or at best very limited, for sentiment annotation. In particular, it provides streamlined multi-dimensional annotation optimized for sentence-level annotation of movie subtitles. Because the platform is publicly available it will benefit anyone and everyone interested in finegrained sentiment analysis and emotion detection, as well as annotation of other datasets.

  • Language Change Database: a new online resource

    Terttu Nevalainen, Turo Anssi Kalevi Vartiainen, Tanja Inkeri Säily, Joonas Kesäniemi, Agata Anna Dominowska, Emily Öhman

    ICAME journal   40 ( 1 ) 77 - 94  2016.04  [Refereed]

     View Summary

    We introduce the Language Change Database (LCD), which provides access to the results of previous corpus-based research dealing with change in the English language. The LCD will be published on an open-access linked data platform that will allow users to enter information about their own publications into the database and to conduct searches based on linguistic and extralinguistic parameters. Both metadata and numerical data from the original publications will be available for download, enabling systematic reviews, meta-analyses, replication studies and statistical modelling of language change. The LCD will be of interest to scholars, teachers and students of English.

    DOI

  • The Challenges of Multi-dimensional Sentiment Analysis Across Languages.

    Emily Öhman, Timo Honkela, Jörg Tiedemann

    Proceedings of the Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media(PEOPLES@COLING)     138 - 142  2016  [Refereed]

    Authorship:Lead author, Corresponding author

  • Recent Changes in Indefinite Pronouns with Human Reference: A diachronic corpus study of 200 years of -one/-body and -man indefinite pronoun variation in Late Modern and Present-day English

    Emily Ohman

       2015

    Authorship:Lead author

  • European intercultural workplace: Sverige

    Allwood, Jens, Lindstr{\"o}m, Natalia Berbyuk, B{\"o}rjesson, Margreth, Edeb{\"a}ck, Charlotte, Myhre, R, i, Voionmaa, Kaarlo, {\"O}hman, Emily

       2007

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Works

  • FEIL (Finnish Emotion Intensity Lexicon)

    Emily Ohman  Other 

    2020
    -
    2021

  • SELF (Sentiment and Emotion Lexicon for Finnish)

    Emily Öhman  Other 

    2020
    -
    2021

  • XED multilingual emotion-annotated dataset

    Emily Ohman, Kaisla Kajava, Marc Pàmies, Jörg Tiedemann  Database science 

    2020
    -
    2021

  • Sentimentator (dockerized sentiment annotation tool)

    Emily Ohman, Kaisla Kajava  Software 

    2018
     
     

Awards

  • Small grants

    2020.11   European Association for Digital Humanities   Python for digital humanities

  • Future Digileader

    2020.11   KTH Royal Institute of Technology, Digital Futures research center, Sweden   Future Digileader

Research Projects

  • Negative emotions in literature: a computational approach to tone and mood

    JSPS  Early Career Researchers

    Project Year :

    2022.04
    -
    2024.03
     

  • Establishing Japanese Natural Language Processing for Digital Humanities at SILS

    Waseda University  Tokutei Kadai - research base creation

    Project Year :

    2022.06
    -
    2023.03
     

  • Applied NLP: Creation of an interactive on-demand programming course for practical NLP

    Waseda University  Tokutei Kadai

    Project Year :

    2022.04
    -
    2023.03
     

  • Digital Humanities and Interdisciplinary Research

    Waseda University  Tokutei Kadai - research base creation

    Project Year :

    2021.06
    -
    2022.03
     

  • Unconventional Communicators in the COVID crisis

    Helsingin Sanomain Saatio 

    Project Year :

    2020
    -
    2022
     

    Salla-Maaria Laaksonen, Juho Paakkonen, Emily Ohman, Essi Poyry,Hanna Reinikainen

  • Intimacy in Data-driven Culture

    Academy of Finland 

    Project Year :

    2020
    -
    2021.03
     

    Anu Koivunen, Kaarina Nikunen

  • Salaried PhD position

    University of Helsinki 

    Project Year :

    2016.01
    -
    2020.11
     

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Presentations

  • SELF & FEIL: Emotion lexicons for Finnish

    Emily Ohman

    Digital Humanities in the Nordic and Baltic Countries 

    Presentation date: 2022.03

  • The Validity of Lexicon-based Emotion Analysis in Interdisciplinary Research

    Emily Ohman

    NLP4DH @ ICON'21 

    Presentation date: 2021.12

  • Japanese Beauty Marketing on Social Media: Critical Discourse Analysis Meets NLP

    Amy Grace Metcalfe, Emily Ohman

    NLP4DH @ ICON'21 

    Presentation date: 2021.12

  • What to expect from an academic career?

    Maryam Elahi, Naveen Bagalkot, Emily Ohman  [Invited]

    Future Digileaders 

    Presentation date: 2021.10

  • Skin Deep: Exploring ideals of Japanese beauty through social media

    Amy Grace Metcalfe, Emily Ohman

    Japanese Association for Digital Humanities Conference 2021 

    Presentation date: 2021.09

  • Panel: Current approaches to Digital Humanities. Researches of the EADH Small Grants 2020 recipients

    Rada Varga, Anna-Maria Sichani, Merisa Martinez, Emily Ohman, Annamária –, Izabella Pázsint, Gamze Saygi, Oksana Maistat, Ilia Uchitel, Kathryn Simpson  [Invited]

    European Association for Digital Humanities 

    Presentation date: 2021.09

  • AI Ethics and Applications in Finance

    Emily Ohman  [Invited]

    INDEX Varainhoito 

    Presentation date: 2021.09

  • AI for the Environment

    Emily Ohman  [Invited]

    Finnish Environment Institute 

    Presentation date: 2021.02

  • Challenges in Annotation: Annotator Experiences from a Crowdsourced Emotion Annotation Task

    Emily Ohman

    Digital Humanities in the Nordic Countries 

    Presentation date: 2020.10

  • Emotion Preservation in Translation: Evaluating Datasets for Annotation Projection

    Emily Ohman, Kaisla Kajava

    Digital Humanities in the Nordic Countries 

    Presentation date: 2020.10

  • Workshop leader on minimizing bias in machine learning algorithms

    Emily Ohman

    Rajapinta days (computational social science conference) 

    Presentation date: 2019.11

  • Towards the Inevitable Demise of Everybody? A multifactorial analysis of -one/-body/-man variation in indefinite pronouns in historical American English

    Emily Ohman, Tanja Säily, Mikko Laitinen

    ICAME40 

    Presentation date: 2019.06

  • Teaching Computational Methods to Humanities Students

    Emily Ohman

    Digital Humanities in the Nordic Countries 

    Presentation date: 2019.02

  • Introducing Sentimentator for Social Sciences

    Emily Ohman

    Rajapinta days (computational social science conference) 

    Presentation date: 2018.11

  • Multilingual Emotion Analysis

    Emily Ohman

    DigHum: Academy of Finland & JSPS 

    Presentation date: 2018.11

  • Creating a Dataset for Multilingual Fine-grained Emotion-detection Using Gamification-based Annotation

    Ohman Emily

    EMNLP 

    Presentation date: 2018.10

  • Computational Bias and AI Ethics

    Emily Ohman  [Invited]

    AI in Education @ Stanford University 

    Presentation date: 2018.10

  • Sentimentator: A Sentiment and Emotion Annotation Platform

    Emily Ohman, Kaisla Kajava

    Digital Humanities in the Nordic Countries 

    Presentation date: 2018.03

  • Mitigating Bias in Machine Learning Applications

    Emily Ohman

    AI in Education @ University of Helsinki 

    Presentation date: 2018.02

  • The Challenges of Multi-dimensional Sentiment Analysis Across Languages

    Emily Ohman

    CoLing 

    Presentation date: 2016.12

  • Lexicon-based Multilingual Sentiment Analysis

    Emily Ohman  [Invited]

    FIN-CLARIN 

    Presentation date: 2016.06

  • "Language Change Database: a new online resource"

    Emily Ohman, Agata Dominovska

    From Data to Evidence 

    Presentation date: 2015.10

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Specific Research

  • Digital Humanities and Interdisciplinary Research

    2021   Amy-Grace Metcalfe, Elissa Nakajima Wickham

     View Summary

    The Tokutei Kadai research grant allowed me to set up a research base for interdisciplinary collaborative research at Waseda University, specifically SILS and GSICCS, which resulted in several projects, publications, and conference presentations. Specifically, we collected and modeled social media data on Japanese beauty ideals and hate speech moderation, combining my computational expertise with subject matter expertise at SILS and GSICCS. Furthermore, I was able to start collaborative work between Waseda University and researchers from other Japanese universities such as Kyoto University, Tokyo University, and Chiba University and presented some of my work at the Japanese Association for Digital Humanities conference.This research fund also allowed me to set up a research base and conduct the necessary preliminary research to be able to secure a JSPS Kakenhi grant for the years 2022-2024.

 

Syllabus

Teaching Experience

  • Social Media and Data Analysis

    Waseda University  

    2021.09
    -
    Now
     

  • Python Programming for Digital Humanities

    Waseda University  

    2021.04
    -
    Now
     

  • Introduction to Digital Humanities

    Waseda University  

    2021.04
    -
    Now
     

  • Methods for Digital Humanities

    Waseda University  

    2021.04
    -
    Now
     

  • Citizen Science: Crowd-sourcing as a Tool for Collecting Quantitative and Qualitative Data

    University of Helsinki  

    2021.01
    -
    2021.04
     

  • Digital Intimacy: Media, habits, and affect.

    Tampere University  

    2021.02
     
     
     

  • Introduction to Language Technology

    University of Helsinki  

    2014.09
    -
    2020.12
     

  • Methods in Digital Humanities

    University of Helsinki  

    2016.09
    -
    2016.12
     

  • Modeling Meaning and Knowledge

    University of Helsinki  

    2016.01
    -
    2016.06
     

  • Project Course in English Linguistics

    University of Helsinki  

    2015.01
    -
    2015.06
     

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Committee Memberships

  • 2021.04
    -
    Now

    Waseda University  Statistics Education Committee

  • 2017
    -
    2021

    University of Helsinki  Ethics committee

  • 2017
    -
    2021

    University of Helsinki  Teaching Evaluation Committee

Media Coverage

  • Lectio praecursoria: The Language of Emotions

    Internet

    Rajapinta ry. (Computational social science academic society)  

    https://rajapinta.co/2021/04/30/lectio-praecursoria-the-language-of-emotions/  

    2021.04

  • New methods improve analysis of emotional content in text

    Internet

    Author: Other  

    Finnish National News Agency (STT)  

    https://www.sttinfo.fi/tiedote/uusilla-metodeilla-voi-analysoida-tekstin-tunnelatauksia-entista-paremmin?publisherId=3747&releaseId=69902466  

    2021.02

  • The digital as fieldwork for historical researchers

    Internet

    Author: Other  

    https://journal.fi/ennenjanyt/article/view/108931/63923?acceptCookies=1  

    2018

Academic Activities

  • Program committee member, NLP4DH

    Competition, symposium, etc.

    2021
    -
    Now
  • Peer review for IEEE Transactions on Affective Computing

    Peer review

    2022.04
    -
     
  • Peer review for DHNB

    Peer review

    2021
     
     
  • Peer review for NoDaLiDa

    Peer review

    2019
    -
    2021
  • Peer review for DHNB

    Peer review

    2019
    -
    2021
  • Member of steering group for digital development at the University of Helsinki

    Other

    2018
    -
    2021
  • Peer review for EMNLP

    Peer review

    2020
     
     
  • Peer review for EACL

    Peer review

    2020
     
     
  • Peer review for NAACL-HLT

    Peer review

    2019
     
     
  • MA thesis award committee

    Competition, symposium, etc.

    2018
     
     
  • Team leader of DH Hackathon

    Competition, symposium, etc.

    2017
     
     

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