New publication on automation in journalism

In a new article published in Russian professional journal Zhurnalist, Olga Dovbysh outlines three key insights from the current academic debate on news automation that are relevant for Russian newsrooms.

The article is available on the Zhurnalist website: ‘Автоматизированная журналистика глазами академических исследователей’

Olga Dovbysh is a postdoctoral researcher of the project ‘Towards Sustainable Journalism for the Algorithmic Future’, funded by the Helsingin Sanomat Foundation and lead by Mariëlle Wijermars.

CfP: Special issue ‘Algorithmic Governance in Context’

Special issue of New Media & Society

We invite paper proposals for a special issue in the journal New Media & Society that will interrogate the functions and effects of algorithms in contemporary governance. Contributing to the current academic debate, the special issue seeks to conceptualize the notion of context in algorithmic governance by, first, perceiving of algorithmic governance as an activity taking place in a variety of contexts and aiming at investigating these contexts in a systematic manner. Second, by focusing not only on how algorithms are used as tools for governance, but also on how such tools can be governed – controlled and held to account – and what challenges such forms of governance imply. The use of algorithms in society can imply a moving of contestable issues from negotiable to non-negotiable spaces, thereby reducing agency and influence of human actors. Active recontextualizations can become an important tool to problematize such and other consequences of algorithmic governance and reveal possible unintended implications and effects.

The special issue builds upon a series of workshops (2019-2020) facilitated by a networking grant from The Joint Committee for Nordic Research Councils in the Humanities and Social Sciences (NOS-HS) coordinated at the University of Helsinki, that focused on the multiplicity of contexts in which algorithmic systems operate. Drawing upon the conceptual work conducted during the workshops, the special issue focuses on two key themes: multiplying the contexts of algorithmic governance and governing algorithms in context.

Multiplying the contexts of algorithmic governance

Articles are invited that explore how specific conditions impact upon the efficacy and perceived legitimacy of algorithms as tools for governance. In particular, contributions may direct attention to the manifold everyday practices through which algorithmic governance is effectuated and investigate the legal, political, cultural, economic, and technological frames that predispose and tacitly guide these. Through this focus, it becomes clear that algorithmic governance is not only a deeply contextual activity, but also an activity carried out within the frames of a multiplicity of different and often competing contexts. Identifying exactly which contexts matter when, in which ways, and to whom becomes an important task for the planning of algorithmic forms of governance in and through autonomous machine learning systems. At the same time, active recontextualization enables problematizing and resisting algorithmic governance in cases where it is perceived as illegitimate or biased.

Governing algorithms in context

Articles are invited that focus on the fact that algorithms at once govern, and are themselves governed by, either human or non-human agents. The increased use of algorithms in all areas of life makes the question of how to understand and sufficiently control such governing algorithms a timely and salient area of critical inquiry. Issues such as the complexity and opacity of algorithmic assessment and feedback systems as well as their growing autonomy and pervasiveness are important areas of research dedicated to improving the governance of algorithms. Articles could, for example, aim at facilitating new technical solutions, at raising public awareness, at informing practices of decision-makers and funding bodies, as well as at critically assessing cultural and other responses to the governance of algorithms.

We welcome both disciplinary and interdisciplinary perspectives and studies employing various social scientific methods, including comparative case-studies, ethnography, socio-legal studies, design studies, and historical inquiry. We particularly encourage studies that challenge the status quo, either through innovative (mixed method) methodologies or critical reflections on the state of the art. Papers could address, but are not limited to, the following questions:

  • What are the different ‘realities’ constructed by the use of algorithms in governance? How do they play out across time and space?
  • How do individuals – in private or organisational contexts – make sense of and respond to algorithmic governance?
  • What are the similarities and differences in the deployment of algorithmic governance within public and private sectors?
  • What are the challenges of developing effective strategies for governing algorithms at the intersection of law and technology?
  • How can different publics be made aware of ‘algorithmic bads’, while still benefiting from ‘algorithmic goods’?

In sum, papers can either systematically tackle the contexts of algorithmic governance or investigate the governance of algorithms, identifying challenges that emerge in different governance contexts.

Guest editors:

Daria Gritsenko, Assistant Professor in Russian Big Data Methodology, University of Helsinki.

Annette Markham, Professor of Media & Communication, Digital Ethnography Research Centre, RMIT, Melbourne.

Holger Pötzsch, Professor of Media- and Documentation Studies, UiT – The Arctic University of Norway.

Mariëlle Wijermars, Assistant Professor in Cyber-Security and Politics, Maastricht University.


Submission guidelines:

Proposals of 750-1000 words should include an abstract and a short description explaining how the proposed paper relates to the special issue theme. Please submit your proposal through the submission form no later than June 30, 2020. Invited paper submissions will be due 31 October 2020 and will undergo peer review following the usual procedures of New Media & Society. Approximately 10-12 papers will be sent out for full review. Therefore, the invitation to submit a full article does not guarantee acceptance into the special issue. The special issue is scheduled for publication in early 2022, with online first publication expected from mid-2021 onwards.

Workshop “Words and Actions. Political text mining” – January 13-14

Workshop “Words and Actions. Political text mining” January 13-14, 2020, University of Helsinki, Finland

The “Words and Actions” project hosts a two-day international workshop on advanced methods of textual analysis used to address complex and theoretically rich questions coming from sociology, political science and history.

The workshop focuses on three methodological approaches to texts. First, it presents novel techniques of supervised machine learning applied for automated annotation of texts. These techniques enable scaling up of theory-rich qualitative research approaches, such as discourse network analysis. The second approach introduces quantitative methods of semantic analysis as tools for a fine-grained study of social and political change used by conceptual historians and political sociologists. Third, the workshop aims at exploring the use of vector representations of textual data – such as word embeddings –for nurturing research which takes into account multi-dimensionality of cultural and political space.

Attendance is free. Please register by clicking here

Venue: University of Helsinki, Unioninkatu 33, room 303 (entrance from Unioninkatu)

Contact: Juulia Heikkinen (

Organizer: Andrey Indukaev (

Funded by the Future Development Fund, Faculty of Arts, University of Helsinki


January 13

8.30 – Welcome coffee and snacks

9.00-9.15 – Opening words. Andrey Indukaev (University of Helsinki)

9.15-11.45 – Session 1. Quantitative conceptual history

Jani Marjanen (University of Helsinki): The case for quantitative conceptual history

10.00-10.20 – Coffee break

Paul Nulty (University College Dublin): Word association measures for building semantic networks

Lidia Pivovarova (University of Helsinki): Political term clustering for historical newspaper analysis

12.00-13.00 – Lunch break

13.15-17.45 – Session 2. Automating annotation and discourse networks analysis

Félix Krawatzek (ZIOS Berlin): Tracing shifting meanings of youth through discourse network analysis

Erenay Dayanik (University of Stuttgart): Towards computational construction of discourse networks for political debates

14.45-15.15 – Coffee break

Nico Blokker (University of Bremen): Semi-automatic construction of discourse networks from newspaper articles

Gregor Wiedemann (University of Hamburg): Active learning for text classification: lessons from automated content analysis of party manifestos and Facebook user comments

Veikko Eranti (University of Helsinki): Going Overboard: Politicization in an anonymous online community.

January 14

9.00-11.45 – Session 3. From vector representations of words to multi-dimensional space of political discourse?

Måns Magnusson (Aalto University): Using priors to capture concepts of interest in large corpora

9.45-10.15 – Coffee break

Kirill Maslinsky (Higher School of Economics, Saint-Petersburg): New emotional vectors of the political regime: the case of Khrushchev’s Thaw in children’s literature

Andrey Indukaev (University of Helsinki): Mapping ideational change in the political space with word embeddings: the case of ‘Modernization’ in contemporary Russia

12.00-13.00 – Lunch break

13.15-15.30 – Session 4. Quantifying evaluation and justification

Daniel Knuchel (University of Zurich): Conzeptualizations of ‘New’ AIDS in German-speaking Discourse – Corpus Linguistic Studies

Eeva Luhtakallio (University of Helsinki) & Jyrki Rasku (University of Tampere): ImagiDem: Visual politicization and deep learning

Andrey Indukaev (University of Helsinki): Automating complex theory-driven annotation: experimenting with Justification Theory

15.30-16.00 – Coffee break

Markets of tomorrow and “great Russia” politics

Andrey, you just came back from the SASE’s 30th Anniversary Conference at The New School in New York. Could you briefly tell us what it was about?


SASE – Society for the Advancement of Socio-Economics – is a large international organization that brings together researchers exploring the economy and society nexus. Its annual conference is the most important venue for this interdisciplinary research domain. This year, the conference theme was “Fathomless Futures: Algorithmic and Imagined”, which spiced the common SASE themes with a focus on digital technology and future oriented activities. This big conference included numerous panels regrouped in 18 networks and 19 mini-conferences – close to 40 tracks in total! I presented a paper at the mini-conference entitled “Futures and Visions of Global Orders” organized by Jenny Andersson, Vincent Cardon, Melissa Fisher, and Olivier Pilmis.

What was your paper about?


The ideational dimension of policy-making is one of my research interests since my doctoral  dissertation, where I analyze how ideas influence the adoption and functioning of market-oriented policy tools in the science, technology and innovation (STI) domain in Russia. This year’s conference focus inspired me to pursue this analysis and to focus on crucial component of ideational context of the policy-making in the STI domain, the images of the future.

What are the main findings of your research?


First, my paper enhances the understanding of the ways of representing the future that widely shared by the country’s political and administrative leadership. I think that the most important result is how country-specific visions of the future, centered on what may be called “great Russia” politics, are intertwined with the investment professionals’ – namely venture capitalists (VCs) – vision of the future, that is spread all over the world. Russian policy in the STI domain has among its objectives serving the “great Russia” politics, that is, reinforcing the country’s standing in international relationships. In this regard, the policy is in line with what the dominant part of political leadership, especially conservative, believe to be the country’s strategic priorities. The corresponding image of the future is the one where Russia struggles for its place in the international relationship system, in particular, through resisting the technology-fueled dominance of the West. In apparent contradiction with this image, the policy tools used in Russia in the STI domain are in line with Western “best practices”, being market-oriented and using venture capital ways of doing as a key reference. My main contribution is to show that there is no great contradiction between the images of the future coming from the venture capital industry and those dominated by the “great Russia” logic. Why is it so? First, the venture capital’s perspective on the future is centered on the revolutionary technologies and products that radically transform – “disrupt” – existing markets and create new ones, thus changing the world. This idea implies that economic actors face the imperative of leading or facing this endless disruption in order not to be whipped out of the markets of tomorrow. Second, the “great Russia” politics nowadays frames the economic sphere as a key battlefield where the country has to consolidate its power. The country’s activities in the STI field framed as a fight for a decent share of the markets of tomorrow (and consequently for its standing in the world) blends the venture capital perspective with the “great Russia” politics.

Putin’s words that the one who will master Artificial Intelligence, will master the Universe made news. But what are the arguments that the president uses to support his claim? In other speeches, the country’s leader referred to the future volume of AI-related market to support his argument about the strategic importance of this technology. My analysis explains how markets and the “mastering of the universe” are intertwined in the images of the future of the Russian political leadership.

What are your plans regarding this line of research?


The next step is to put my analysis in context, since the association between the politics of international competiveness and the STI policy, in particular the mobilization of the venture capital, is not unique to Russia. Just as Russia, China actively uses venture capital to achieve strategic goals, primarily the country’s competiveness in the world economy, blending the future imaginaries of the nation’s rise to power with those of technological development. Similarly, Western democracies justify many State-supported initiatives in the STI domain by mobilizing the catch-up rhetoric, implying that investment in new technologies is key to the country’s standing in the future world order – as it was in the case of the National Nanotechnology Initiative in the US. Thus, I am motivated to show that the Russian case I presented at SASE is not exceptional.

Anna Belokur joins DRS to work on her MA thesis

The DRS team has a new member – Anna Belokur who will be working on her master thesis under the supervision of Prof. Daria Gritsenko. Anna has started her MA in Russian Studies (MARS) programme at the University of Helsinki in September 2018 after taking her bachelor’s degree in biology. Anna’s special interest is public health and she hopes to combine natural and social sciences in the examination of public health and disease in Russia. Her master thesis focuses on the digital trail of Russia’s HIV epidemic, using big data methods to examine the ways in which HIV is present in (or absent from) Russian media discourse, and if/how the relative rates of media «awareness» regarding HIV correlate to rates of reported infections and deaths in various regions.

DRS seminar: closing spring series. Social networks in Soviet film industry; Digitalization of education in Russia

The last seminar of the spring series took place on June 7th, featuring presentations by Nelli Piattoeva, Associate Professor at the University of Tampere, and  Joan Neuberger, Professor at the University of Texas at Austin. The presentation by Nelli Piattoeva entitled “Digitalizing education in Russia: a governance perspective” was focused on an ongoing research project. The digital technology are playing the increasingly important role in the governance of secondary education in the Russian Federation. In particular, more and more information is used for the educational organization monitoring and assessment by the sector’s administration. The resulting changes in how schools function in the new “datified” governance context are being actively investigated by the project’s researchers.

“Social Network Analysis and the Soviet Film Industry” – the presentation by Joan Neuberger – exposed intermediary results of a research project where quantitative methods were used to advance research on the Soviet culture. Joan used open data on Soviet movies* credit scores to analyze the structure and dynamics of the system of collaboration networks in the Soviet cinematographic universe, from its inception to the first post-war decade. The project, led by a specialist in humanities with a cautionary approach towards methodology, exposed the opportunities and limitations of social network analysis in the historical studies of the cultural production. For example, the study of the centrality measures of the collaboration networks revealed an interesting phenomenon: the most “central” characters are not the ones who are the most famous or successful, but those who have the longest track record. That shows that centrality measures should be used with caution when trying to detect prominence within a cultural field, suggesting, at the same time, that social network analysis can reveal actors of great social importance who stayed out of the spotlight.

The closing session of the seminar highlighted the virtues of the Digital Russia Studies seminar, which brings together researchers with different backgrounds wishing to present projects at different stages of advancement, using wide variety of methods, but always sparking interesting and fruitful discussion. Stay tuned for the autumn’s series of the DRS seminar!

Vladimiv Uralskiy (on the left) – the most central actor in the Soviet film industry. Do you know this prolific character actor?

A DH perspective on sub-national governance in Russia

On May 17th, Digital Russia Studies spring seminars series featured two presentations on sub-national governance in Russia – both using digital humanities methods.

DRS co-founder, Daria Gritsenko, introduced the new research project “Algorithmic Governance in Context(s): Civic technology in Russian regions”. This project led by Daria Gritsenko and Andrey Indukaev studies the digitalization of local governance in Russia. The project aims to understand what makes local administrations implement digital tools of civil participation (civic tech) in the Russian regions. The key hypothesis of the project is that there is no single pathway to civic tech uptake, but the reasons vary between the regions: some do it because of the local administration’s interest in digital tools, while others respond to the ‘push from below’ – the needs of the local civil society. The seminar participants discussed the key social and political phenomena that may influence civic tech use, the relevant variables, such as the activity of local media and civil society.

Andrey Starodubtsev presented a his project focusing on the ideational dimension of regional politics in Russia.  The main methodological focus of the project is on the diachronic and synchronic textual analysis of governors speeches and writings. What ideas do regional leaders express in different contexts? In particular, how do they express the desirable status of subnational units? To answer these questions, he aims at analysing the centralist and federalist ideas in governors’ political communication using mixed-method techniques combining text mining and close reading. After the presentation, the discussion turned around the methodological issues of textual analysis, in particular how to approach different types of data and how to deal with unbalanced corpora.

Algorithmic Governance: In search for Context

On 9-10 May 2019, Digital Russia Studies co-founders Dr. Daria Gritsenko and Dr. Mariëlle Wijermars together with the Department of Information Technology at the University of Uppsala organised a multidisciplinary two-day workshop “Algorithms in Context – Towards a Comparative Agenda for Studies of Algorithmic Governance Across Politics, Culture, and Economy.” This workshop was the first in a series of three events scheduled for 2019-2020 and funded by Joint Committee for Nordic research councils in the Humanities and Social Sciences (NOS-HS).

The participants of the first NOS-HS workshop “Algorithms in Context”

IR: Daria, could you tell us how did you come up with the idea of the workshop series?

DG: It was in late 2014, Matt Wood, one of the workshop’s core participants, and I were both fresh PhD graduates in public policy and were debating what will happen to governance in the next few years. We were somehow fascinated by the idea that governance process is increasingly being outsourced – but not to the markets and networks as it has been happening in the course of neoliberal reforms, but to technology and smart algorithms. A couple of years later we met at one of the large political science conferences and realised that the idea of algorithmic governance has picked up speed. It felt like a good time to look at the emerging phenomenon of algorithmic governance from a multidisciplinary perspective. So when Mariëlle asked me whether I would be interested to explore some idea through a series of Nordic workshops, I knew exactly what I wanted to focus upon. We already had links to the University of Tromsø through Prof. Holger Pötzsch and soon we got acquainted with Prof. Francis Lee and Dr. Mikael Laaksoharju. We had a lot of brainstorms, teleconferences, bouncing ideas, and eventually, a funded workshop proposal.

IR: Sounds breath-taking! Can you tell a bit more about the first workshop?

DG: The first workshop  was called ‘Developing a framework for comparative analysis of algorithmic governance’ and it brought together thirteen scholars with background in media, law, politics, area studies and computer sciences from Finland, Germany, the Netherlands, Sweden and the UK to discuss how algorithms interact with contexts and how that could be studied.

During the first workshop, the intensive brainstorming included dividing into three discussion groups and writing a collaborative review article anonymously. In this review, we focused on such questions as: How do we define data and smartness? What are the challenges of machine learning and automated decision making? How is context created for algorithms?

In addition, we had a chance to visit Social Robotics Lab and see algorithms’ working in practice.  That was very exciting – but also sobering. We are much further from the strong AI than the media and entertainment industry are picturing.

“Academic Anonymous” – an innovative simultaneous collaborative writing workshop

IR: What was participants’ opinion on the workshop?

DG: Generally, their expectations were met. The participants were positively surprised how efficient we were during the workshop and found ways of working well-balanced. Our programme was comprehensive, for some a bit too packed, but we really managed to develop a sense of identity as a group and to come up with a draft of a review article. Pretty neat!

IR: So, what’s next on the agenda?

DG: The next workshops are scheduled for autumn 2019 (Helsinki) and spring 2020 (Tromsø). We are all looking forward to next workshop that will be held at the University of Helsinki to start developing collaborative research focusing on specific cases.

IR: Ilona Repponen, DG: Daria Gritsenko

DRS seminar April edition

In the April edition of DRS seminar, Pihla Toivanen introduced her Master’s thesis “Computational Frame Analysis of Populist Counter Media”. Her research is a part of the project “Information chaos and trust in traditional journalism” project carried out at Tampere University’s COMET Research Center in collaboration with Aalto University.

Pihla uses machine learning to study how Finnish populist media builds trust by referring to external information sources. In particular, populist media actively use news coming from traditional media to produce their own content (see table below). Mainstream media in Finland are trusted, and reusing their stories may help populist media to build credibility. However, populist media do not merely reproduce information from the traditional media, but actively reframe it. Pihla developed a supervised machine-learning algorithm that detects how populist media reframe stories from traditional media. The algorithm and the preliminary results of its application to unlabeled data were presented at the seminar, as well as the researcher’s future plans to develop the classification technique. After the presentation, seminar participants discussed the use of machine learning in media studies and new methodologies of media research.

HSS awards grant for ‘Sustainable Journalism for the Algorithmic Future’

Helsingin Sanomat Foundation has awarded a €130,000 grant to DRS co-founder Mariëlle Wijermars for the project ‘Sustainable Journalism for the Algorithmic Future’ (2020-2022).

The project, that in addition to Mariëlle involves Russian Media Lab researcher Olga Dovbysh, will be launched next January and run for three years (short summary below). If you are interested in getting involved or would like to know more, get in touch!

‘Sustainable Journalism for the Algorithmic Future’ (2020-2022)

The project investigates how data-driven media practices and the increased influence of IT industries on media business affect journalism and its role in the public sphere. Integrating new evidence from a hybrid media system (Russia) into a comparative study, it helps understand the context-specificity of this impact and will formulate a vision on making journalism societally, economically and ethically sustainable for the algorithmic future.