Reconstructing Crisis Narratives for Trustworthy Communication and Cooperative Agency
Collaborative research project between Aalto University and Finnish Institute for Health and Welfare (THL)
Project funded by a three-year grant from the Academy of Finland, 2020 – 2023
Update (Feb 9, 2021): Team members include Jonas Sivelä, Anna Leena Lohiniva, Teemu Leinonen, Tuukka Tammi, Suvi Hyökki, Matti Nelimarkka, Johanna Kaipio, Natalia Villaman, Hasti Narimanzadeh, Minttu Tikka, Henna Paakki, Kaisla Kajava, and Talayeh Aledavood.
The emergence of a crisis is often accompanied by unexpected events, uncertain signals, malicious misinformation, and conflicting reports that must be collectively interpreted and analyzed to understand the complex nature and scope of the situation, and its potential implications for society. This research jointly conducted between Aalto University and THL proposes to analyze and reconstruct crisis narratives using mixed-methods, combining qualitative research for narrative inquiry with computational data analytics of crisis discourses in news and social media among diverse publics.
The research will develop a narrative analysis of the COVID-19 pandemic from February 2020 onwards in Finland (in relation to the global discourse); this will serve as the primary case study for this project. In particular, the research will highlight the key narratives, public anxieties, perceptions of risk, misconceptions, values and trust in official guidelines, news/media coverage, and the societal deliberations. It will primarily be focused around mobility restrictions and social distancing measures imposed over distinct timeframes across the unfolding trajectory of the crisis. This would offer a conceptual framework for risk perception and trust in pandemic crisis situations for use by THL, though it could be expanded to other crisis contexts.
We will design a platform representing and visualizing such information to engage decision-makers, front-line responders, stakeholders, and the general public in making sense of crises and perceptions of risk and trust. This will be based on the narrative analysis and participatory design research conducted with stakeholders and public participants. The novel timeline-based prototype tool will allow browsing, searching, and unraveling information for selected crisis themes and narratives. Temporal interactive visualization of crisis narrative threads will be used to support participatory narrative building and multiple hypotheses, facilitate discovery of unusual patterns, and collaborative sense-making. An evaluation of the platform with participants in a pilot study with the THL will offer insights on how such temporal crisis narratives can be used for making sense of perceptions of formal crisis communications, news/media coverage, and informal social media engagement, while improving risk communication and cooperative models for crisis preparedness and response.
Call for Recruitment: Seeking PhD and Postdoc Researchers:
Reconstructing Crisis Narratives for Trustworthy Communication and Cooperative Agency
Principle Investigator: Nitin Sawhney, Professor of Practice, Department of Computer Science, Aalto University
https://research.aalto.fi/en/persons/nitin-sawhney
The research project, jointly conducted between Aalto University and the Finnish Institute for Health and Welfare (THL), proposes to analyze and reconstruct crisis narratives using mixed-methods, combining qualitative research for narrative inquiry with computational data analytics of crisis discourses in news and social media to understand global pandemics. We are seeking Postdocs and PhDs to work at the intersection of Human-Computer Interaction (HCI), design research, computational social sciences, and public health for critical societal impact. We expect the candidate to have background in computer science, media and communication studies, social science, or similar disciplines.
Potential duties and tasks may include the following (to be conducted as part of the research team):
1. Examining the narratives emerging in crisis-related communication using qualitative research methods across various data sources including organization communications, news/media coverage, and social media exchange among diverse publics.
2. Automating content analysis for narrative work using suitable machine learning techniques for Natural Language Processing (NLP) such as Conversation Analysis, Content Classification, and/or Sentiment Analysis. This includes collecting and curating datasets, devising suitable methodologies, setting up the research infrastructure and tools, and a pipeline for data extraction, analysis and validation.
3. Representing and visualizing crisis narratives to support understanding and collaborative sensemaking among key stakeholders and diverse publics. These tools should support browsing, searching, and exploring information for selected crisis themes and narratives. Work in this area includes not only developing prototypes of visualizations, but also conducting design research, user experience (UX) evaluation, and pilot assessment of such tools.
The candidate is not expected to master all these domains, but work closely with a multi-disciplinary research team to lead design and development efforts, while learning and contributing to ongoing work in specific research areas of interest.
The position belongs to the Aalto career system and the selected person will be appointed for a two-year fixed term appointment with an option for renewal.
Supervision: Nitin Sawhney (Aalto University), potential other supervisors: Teemu Leinonen (Aalto University), Nelimarkka, Matt (University of Helsinki), Sivelä Jonas (THL)
Keywords: Crisis Informatics, Computational Social Science, Machine Learning, Conversational Analysis, Information Visualization, Qualitative Research, Participatory Design
Diverse candidates (including women and minorities) are encouraged to apply with a resume and letter of interest.
Update (Feb 3, 2021): The current openings have now been filled, but if new positions emerge we may make this call active again.
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