All workshops have a US$10 fee applied charged during registration. If you are accepted into one of the application-only workshops you will receive an invoice in your email for this US$10 charge. This fee must be paid in advance in order to confirm your attendance of the workshop. This does not apply to the Doctoral Colloquium.
In order to attend a workshop you do have to register for the full conference. Conference registration is available at this link.
Morning – Half Day Workshops
Afternoon – Half Day Workshops
Full Day Workshops
Jonathan Roberge, Michael Castelle, and Thomas Crosbie
Machine learning (ML), deep neural networks, differentiable programming and related contemporary novelties in artificial intelligence (AI) are all leading to the development of an ambiguous yet efficient narrative promoting the dominance of a scientific field—as well as a ubiquitous business model. Indeed, AI is very much in full hype mode. For its advocates, it represents a ‘tsunami’ (Manning, 2015) or ‘revolution’ (Sejnowski, 2018)—terms indicative of a very performative and promotional, if not self-fulfilling, discourse. The question, then, is: how are the social sciences and humanities to dissect such a discourse and make sense of all its practical implications? So far, the literature on algorithms and algorithmic cultures has been keen to explore both their broad socio-economical, political and cultural repercussions, and the ways they relate to different disciplines, from sociology to communication and Internet studies. The crucial task ahead is understanding the specific ways by which the new challenges raised by ML and AI technologies affect this wider framework. This would imply not only closer collaboration among disciplines—including those of STS for instance—but also the development of new critical insights and perspectives. Thus a helpful and precise pre-conference workshop question could be: what is the best way to develop a fine-grained yet encompassing field under the name of Critical AI Studies? We propose to explore three regimes in which ML and 21st-century AI crystallize and come to justify their existence: (1) epistemology, (2) agency, and (3) governmentality—each of which generates new challenges as well as new directions for inquiries.
In terms of epistemology, it is important to recognize that ML and AI are situated forms of knowledge production, and thus worthy of empirical examination (Pinch and Bijker, 1987). At present, we only have internal accounts of the historical development of the machine learning field, which increasingly reproduce a teleological story of its rise (Rosenblatt, 1958) and fall (Minsky and Papert 1968; Vapnik 1998) and rise (Hinton 2006), concluding with the diverse if as-yet unproven applications of deep learning. Especially problematic in this regard is our understanding of how these techniques are increasingly hybridized with large-scale training datasets, specialized graphics-processing hardware, and algorithmic calculus. The rationale behind contemporary ML finds its expression in a very specific laboratory culture (Forsythe 1993), with a specific ethos or model of “open science”. Models trained on the largest datasets of private corporations are thus made freely available, and subsequently détourned for the new AI’s semiotic environs of image, speech, and text—promising to make the epistemically recalcitrant landscapes of unruly and ‘unstructured’ data newly “manageable”.
As the knowledge-production techniques of ML and AI move further into the fabric of everyday life, it creates a particularly new form of agency. Unlike the static, rule-based systems critiqued in a previous generation by Dreyfus (1972), modern AI models pragmatically unfold as a temporal flow of decontextualized classifications. What then does agency mean for machine learners (Mackenzie, 2017)? Performance in this particular case relates to the power of inferring and predicting outcomes (Burrell, 2016); new kinds of algorithmic control thus emerge at the junction of meaning-making and decision-making. The implications of this question are tangible, particularly as ML becomes more unsupervised and begins to impact on numerous aspects of daily life. Social media, for instance, are undergoing radical change, as insightful new actants come to populate the world: Echo translates your desires into Amazon purchases, and Facebook is now able to detect suicidal behaviours. In the general domain of work, too, these actants leave permanent traces—not only on repetitive tasks, but on the broader intellectual responsibility.
Last but not least, the final regime to explore in this preconference workshop is governmentality. The politics of ML and AI are still largely to be outlined, and the question of power for these techniques remains largely unexplored. Governmentality refers specifically to how a field is organised—by whom, for what purposes, and through which means and discourses (Foucault, 1991). As stated above, ML and AI are based on a model of open science and innovation, in which public actors—such as governments and universities—are deeply implicated (Etzkowitz and Leydesdorff, 2000). One problem, however, is that while the algorithms themselves may be openly available, the datasets on which they rely for implementation are not—hence the massive advantages for private actors such as Google or Facebook who control the data, as well as the economical resources to attract the brightest students in the field. But there is more: this same open innovation model makes possible the manufacture of military AI with little regulatory oversight, as is the case for China, whose government is currently helping to fuel an AI arms race (Simonite 2017). What alternatives or counter-powers could be imagined in these circumstances? Could ethical considerations stand alone without a proper and fully developed critical approach to ML and AI? This workshop will try to address these pressing and interconnected issues.
We welcome all submissions which might profitably connect with one or more of these three categories of epistemology, agency, and governmentality; but we welcome other theoretically and/or empirically rich contributions.
We invite interested scholars to submit proposal abstracts, of approximately 250 words, by 11:59pm on June 30, 2018 to CriticalAI2018 [at] gmail [dot] com. Proposals may represent works in progress, short position papers, or more developed research. The format of the workshop will focus on paper presentations and a keynote, with additional opportunities for group discussion and reflection.
This preconference workshop will be held at the Urbanisation Culture Société Research Centre of INRS (Institut national de la recherche scientifique). The Centre is located at 385 Sherbrooke St E, Montreal, QC, and is about a 20-minute train ride from the Centre Sheraton on the STM Orange Line (enter at the Bonaventure stop, exit at Sherbrooke), or about a 30-minute walk along Rue Sherbrooke.
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Digital Methods for Internet Research
Axel Bruns, Jean Burgess, Tim Highfield, Tama Leaver, Ben Light, and Richard Rogers
This full-day preconference workshop introduces participants to digital methods and their applications in media, cultural and internet studies via a series of short talks, masterclasses, and hands-on methods sessions. The sessions will cover critical topics in Internet Research and related fields, from social media analytics to app studies, fake news and visual social media research. Participants will be supplied ahead of time with learning resources including tutorials, readings and rich media examples. The schedule will also provide opportunities for discussion and practical experimentation. The workshop is designed for internet researchers at all stages of their careers, and will have particular relevance for PhD and early-career scholars. The session will be limited to 50 participants.
Welcome and Provocations for Digital Methods and Digital Media
This introduction sets out the state of play around digital methods and digital media. While some popular platforms, like Twitter, have been extensively studied by internet researchers and offer established methodologies, other platforms create their own ethical, methodological, and conceptual challenges – from Instagram’s changing API access to the prevalence of visual media within digital media communication. The introduction provides provocations for internet researchers, for approaches to digital media research that engage with critical elements of everyday digital media from users to big data to platforms to algorithms.
1. Analysing Social Media Data with Tableau
Especially when working with large social media datasets, visual data analysis is now an indispensable part of the scholarly research and publication process. Data visualisation is able to provide a rapid overview of patterns in the dataset, and to pinpoint specific events and areas that should be selected for further in-depth analysis. The social media data analytics workshop will focus on a key emerging tool for large-scale analysis, Tableau, for processing and visualising large datasets.
2. The walkthrough method for studying apps
Most discussion around digital methods focuses on the analysis of ‘big data’ from social media platforms, but how can we study the platforms themselves? To do so we need to take into account not only their ‘content’ or user ‘behaviors’, but also their socio-technical features, cultures of use, and business models, especially as they co-evolve. However, while software applications (apps) are the site of significant sociocultural and economic transformations across many domains, from health and relationships to entertainment and finance, as relatively closed systems they pose methodological challenges for digital media research. In this session, participants will be introduced to the App Walkthrough, which borrows from digital media culture, User Experience research and STS to undertake an ‘ethnography of affordances’, as part of a broader platform studies approach to mobile dating and hook-up applications. Participants will learn how to establish an app’s environment of expected use by assessing its vision, operating model, and modes of governance. They will also gain hands-on experience using the walkthrough technique to systematically step through the stages of registration, everyday use, and discontinuation to identify the app’s embedded cultural meanings and implied ideal users.
3. Fake News Detection and Network Discovery
The workshop discusses how to study cookies, trackers and third-party elements (using the Tracker Tracker tool) to compare mainstream and so-called fake news sites, thereby detecting differences. It subsequently introduces techniques to reverse lookup Google Analytics and AdSense IDs so as to discover and map fake news websites that are related to each other through ownership. The workshop frames the digital methods for fake news detection and network discovery as contributions to the study and practice of data journalism.
4. Instagrammatics and visual social media
This workshop’s exploration of visual social media uses Instagram as a focus but with applications beyond this specific platform. Making use of shared elements of social media content, such as hashtags, memes, and formal and informal conventions of communication, the methods used in this workshop position visual social media within the wider social media ecosystem. The workshop provides a hands-on means for approaching visual social media, giving participants the opportunity to interrogate what they might do with such data and what visual media and methods might contribute to research. Critical considerations around coding visual data, dynamic data, archival questions, and ethical issues, including privacy, will guide the workshop discussion.
Wrap-up: Challenges and Futures for Digital Methods
This final session will bring facilitators and participants together to reflect upon the methods introduced in the workshop, and to address challenges and needs for digital methods going forward. This discussion will offer participants additional opportunities to discuss issues and questions relevant to digital methods in their own individual research projects.
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Digital Research Ethics Collaboratory for Networked Intimate Publics: Storytelling, Materiality, Ethics & Praxis
T.L. Cowan, Jasmine Rault, Veronica Paredes, and Izetta Autumn Mobley
In The Broken Earth trilogy, science fiction author N.K. Jemisin (2015, 2016, 2017) imagines a subterranean community called Castrima, a hidden place that is built and sustained by the energies and skills of the most powerful, reviled and thus most endangered specimens of humanity: the Oregens. From the surface, Castrima is invisible, buried below ruins. And underground, from the inside, Castrima looks cluttered, chaotic, disorienting: “as if someone found an architect, made her build a city out of the most beautiful materials available, then threw those buildings into a box and jumbled them up for laughs” (2015: 338). Ykka, Castrima’s Head Woman, explains, “This is what we’re trying to do here in Castrima: survive. Same as anyone. We’re just willing to innovate a little” (2015: 342). Jemisin’s speculative design of Castrima is a place made by and for minoritized subjects to protect their lives, to preserve their knowledge and cultural materials, and ensure their cultural survivance (Vizenor 2008; Tuck 2009).
This workshop will be led by former co-facilitators of the Feminist Technology Network (FemTechNet), collaborators in the Center for Solution to Online Violence (CSOV) and lead investigators of the Digital Research Ethics Collaboratory (DREC). We use the term “minoritized” from the scholarly fields of Indigenous, Critical Race and Ethnic Studies, Queer, Sexuality, Trans-, Gender and Feminist Studies, to speak of populations who may not be in the minority at all – indeed, statistically form the majority population in most cases – but whose knowledges, cultural practices, histories and socialities have been consistently undermined, dismissed and rendered insignificant or troubling to the imagined majority (Ferguson 2004; Gopinath 2005; Sedgwick 1990, 2003; Smith 2010; Soto 2010). The infrastructures and networks of intimacy and distributed publicity are central technologies for the sustenance, support, thriving and survivance of minoritized people, knowledges, cultural materials, and chosen communities. These network technologies are too often situated in academic literature and popular discourse as naïvely pre-digital or non-digital, naturally occurring or innate, rather than carefully and strategically constituted, tended-to and transformed with and as new media and communication infrastructures. In this workshop we invite participants to share stories and practices for the ethical research and engagement with minoritized materials and the networked intimate publics that create them. Workshop participants will take turns leading discussions from their own research experiences in attending to the innovations in labour, arts, organizing and research through which technologies for minoritized survivance manifest and mutate.
Like so many researchers we have been caught by the fever to (digitally) archive precarious, precious, minoritized, invisibilized, intimate, forgotten knowledges, scenes, resistance cultures, materials and alternative futures. Bound by their beauty (Siberry 1989), we are also, however, bound by the institutional and platform logics that we hope these archives can transform, and by accountability to the “the people whose belongings have become [our] ‘collections’” (Nowviski 2016). Conventionalised research practices reflect longstanding and ongoing acquisitional, abductive, possessive, extractive practices that bolster these structures, especially the imperialist, settler colonial model of dehumanization, occupation, control, theft, and non-reciprocity (Kovach 2009; Moreton-Robinson 2015; Murphy 2014; Simpson 2014; Tuhiwai Smith 2012).
This workshop comes from the perspectives that all research structures–not only those primarily oriented within or towards Indigenous communities–need to be reshaped in order to decolonize and unsettle the imperialist university and to dismantle the domination habits of academic knowledge production. Starting with the important work that AoIR collaborators have already contributed to the field of Digital Research Ethics (AoIR 2002; Markham and Buchanan 2012; Zimmer & Kinder-Kurlanda 2017), we invite AoIR-affiliated scholars–especially those of digital culture and researchers building online repositories, exhibitions and other forms of publication of minoritized materials–who are trying to break the habits of extractive and possessive research and publication logics and build-while-we-work-within epistemic infrastructures that acknowledge and jumble existing hiearchives of compensation, credit, value, precarity, security and exposure. Following Jemison’s fictional Castrima, the challenge might be to defend against openness and exposure even in opposition to the institutional logics of our disciplines. This workshop will gather researchers who attend to, and attempt to translate into online information practice, the carefully cultivated tactics and cultures of privacy and counter-surveillance which were, and continue to be, necessary to the survival, and survivance, of minoritized people and cultures.
1. This is a half-day workshop. We will begin with 1 hour of presentations by the co-facilitators, followed by 1.5 hours of group workshopping current, past and future projects that participants bring to discuss, and a concluding 30 minutes drafting protocols, manifestos, best-practices and other collaborative (and future) possibilities.
2. AoIR participants can register for this workshop when they register for the conference; please come prepared to either workshop your own project or pitch in to workshop projects that other participants bring.
If you have already registered for the conference and would like to add this workshop please email ac [at] aoir [dot] org . For further information, please contact workshop organizers T.L. Cowan & Jas Rault at email@example.com.
Efrat Daskal, Nicholas John Proferes, Jeff Hemsley, and Andrea Guzman
This half-day workshop brings early career scholars together to address unique issues they face, develop strategies to achieve career goals, and foster a professional network. We define early career scholars as people who have finished the requirements for their terminal degree but have not advanced to the next level in their field or industry (i.e. post-docs, non-tenured faculty, junior industry researchers). AoIR’s strength is its communication. Now in its third year, this workshop acts as a way to foster community among emerging scholars and to create bridges between junior and senior scholars. We aim to continue working toward making this community as inclusive and representative as possible.
The workshop addresses both challenges and opportunities unique to early-career researchers in the many fields and forms of scholarship represented at AoIR. First, we have to negotiate the transition from graduate student to early career professional that requires a higher level of autonomy and the challenge of figuring out the pragmatic and social aspects of a new work environment. Second, we must work quickly to establish ourselves in our fields and, often, secure funding. Third, we have increased service responsibilities. Fourth, after being guided by our advisors and committees for several years, we quickly move from mentee to mentor for our own students. Fifth, we must learn to navigate moving to the next level of our careers while ensuring time with family and friends. Being a junior scholar also comes with unique opportunities that we also will explore. While recognition of internet scholarship has come a long way since AoIR’s inception, junior scholars still may find themselves facing certain hurdles in gaining recognition for their research (i.e. subject, method, etc) in terms of promotion. In fact, some of the challenges we face also are opportunities to work towards changing the ways in which internet scholarship is perceived and valued within the academic structure.
The issues we will cover depends greatly on the participants. AoIR is an international and diverse organization, and we know that our experiences as scholars and educators vary by country, institution type, and field and are framed by our own identities (race, gender, etc). Our goal is to discuss shared challenges and opportunities while understanding differences so that we can build our own professional networks at the same time that we create a diverse and inclusive community of scholars who will eventually become future career mentors within AoIR.
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Shawn Walker, Christian Newman, Kristen Shinohara, Nicholas Proferes, and Emi Moriuchi
Researchers are drawn to the magnitude of social media data available today. Hundreds of studies have been published using Twitter data (Zimmer & Proferes, 2014), as a result of it’s popularity Tufecki (2014) calls Twitter the “model organism” for social media analysis. Yet, Twitter is not a static platform, undergoing numerous changes to its user interface, default settings, affordances for engagement, and algorithms over time. Its API changed each time new data structures were added, and its Terms of Service, Community Rules, and Privacy Policies were collectively revised more than a dozen times.
Twitter data from a decade ago is different than today, and analysis on such data may be inappropriate for current studies. To ignore changes in platform evolution is to compare dissimilar data constructs over time. These questions extend outside of Twitter, for example, Instagram added stories, allowing users to share all posts across a single day. Snapchat added mapping features, later allowing users to access them both inside and outside the mobile application. Rigorous inferences on historical data require an account of platform/data evolution, and a transparent awareness of how this evolution impacts conclusions that we draw from such data.
While social media data used for scientific research opened new opportunities in machine learning and artificial intelligence, allowing for new techniques for investigating large-scale trends, researchers do not systematically address the rapid shifting of the research space. Changing platforms and data restrict conclusions to one point in time, yet researchers do not account for shifts in orientation. How do we account for this amalgamation of data, its evolution and the impact platform and design changes have on the the kinds of data sets produced, analyzed, and the conclusions drawn?
Unfortunately, information about the evolution of these platforms is only available in part. Data such as public tweets, public changes to policy, and visible UI enhancements are disparately available. In contrast, most API, underlying platform performance mechanisms and internal policies that drive system design are private. The lack of systemic information about these changes prevents accurate change comparison. Ultimately, research evolves based on assumptions about the actual state of the data. We will ask participants to tackle the following questions:
How have changes to social media platforms influenced user behavior and vice versa? That is, can we quantify the effect platform evolution has on its users’ perceptions?
How have researchers using social media data contextualized or integrated historical research/citations? How can we develop a theoretical basis or methodology to account for historical data?
How do researchers describe/document the current state of a social media platform under investigation?
What types of documentation are necessary to account for platform changes over time?
Are social media platforms comparable at different points in time?
This workshop is structured to facilitate open discussion of the challenges faced by researchers working with social media archives and knowledge produced about social media that has since aged. The workshop will include brainstorming grand challenges to data analysis on shifting platforms; discussions on case studies and hypothetical methodologies for addressing the issues identified; and identifying ideas to contextualize social media data sets.
The workshop will consist of three main parts:
First, the workshop will open with brief introductory remarks from the workshop organizers and selected participants, laying out what we see as the scope of the problem. (30 minutes)
We will next conduct a fishbowl session to brainstorm the grand challenges of this area. –
What are the dangers of relying on outdated historical data and how do we address this methodologically? (60 minutes)
For the third session, we will split participants up into small groups for an interactive session to develop hypothetical approaches to address the grand challenges. (60 minutes)
Lastly, groups will report back to the audience, identifying the kinds of resources required to make these projects or approaches actually happen. (30 minutes).
The desired output includes the publication of a prioritized roadmap for future research in this area.
Stefanie Duguay and Mia Consalvo
This pre-conference workshop will bring together game studies scholars and social media researchers to discuss the increasing popularity of live digital technologies. These technologies include features on social media sites such as Facebook Live, standalone smartphone apps (e.g., Periscope), and websites dedicated to live streaming, such as the gaming platform Twitch.tv.
Although live streaming has been possible for more than a decade (e.g. Senft, 2008), the evolution of recording devices, data transfer speeds, mobile apps, and other digital technologies has contributed to a recent proliferation of live media. Live platforms encourage spontaneous sharing but controversial incidents raise questions about what should be shared in a live context. Live streaming game platforms showcase modes of self-presentation and self-promotion (Consalvo & Altizer, 2017), which social media influencers also adopt when broadcasting content to adoring fans (Abidin, 2016). Gamers and influencers alike benefit from the commercialisation of these practices, generating revenue from brand promotion and boosting attention to advertisements. Clearly, live streaming and live digital technologies have social, political, economic, and cultural impacts. However, research into these areas is still developing and there have been few opportunities for interdisciplinary dialogue among scholars researching live streaming.
We invite you to tackle these topics with us at this off-site pre-conference workshop, taking place nearby at Concordia University’s cutting-edge Milieux Institute for Arts, Culture and Technology (10-minute walk from the Sheraton Hotel). The day will feature a keynote presentation by Dr. T.L. Taylor, Professor of Comparative Media Studies at the Massachusetts Institute of Technology. Dr. Taylor is an internationally recognized scholar in game studies, having written field-defining books about online games, the rise of competitive esports, and the business of live streaming.
The workshop is open to all and we encourage AoIR members to register through the conference website to reserve your spot. The day will also include paper sessions for presenting and receiving feedback about works-in-progress. We invite abstracts from scholars researching livestreaming and live digital technologies across a range of topics, including but not limited to:
- Gaming and esports
- Platform infrastructures, algorithms, and automation
- Communities, practices, and audiences
- Microcelebrity and self-branding
- Political economies and labour
- Ephemeral and everyday media
- Data, policy, privacy, and governance
- Transnational liveness
Selected presenters will have the chance to submit their work-in-progress papers prior to the workshop for circulation to attendees. If you are interested in presenting, please submit an abstract of 250 words along with your name, title, affiliation and a brief bio (50 words) to goingliveconf [at] gmail [dot] com by June 29, 2018.
Nina Duque, Guillaume Latzko-Toth, Florence Millerand, and Rémi Toupin
Learning expeditions and collaborative knowledge research are but a few of the terms used to describe open walked event-based experimentations (OWEEs). Born out of a desire to transcend traditional practices of academic writing and conference attendance, OWEEs seek to create, through action-oriented work and collaborative methods, innovative learning times and novel sharing spaces. In short, to try to “think otherwise” by changing the way we learn. Combining ethnography with more transformative research designs, learning expeditions contribute to the understanding of knowledge production and sharing through a three-pronged conceptual approach (de Vaujany, 2018): 1) corporeal engagement and embodiment through walking and moving within a space, 2) performativity and visuality of public space-time and, 3) assemblage of narratives and engaged texts. Within this theoretical framework, learning becomes a constructed relationship, a process of “making” rather than “imparting.” Learning is based on shared practices and supported through web-enabled networked productions and texts. A learning expedition brings together people of different scholarly communities through the exploration of third places (spaces and times that are separate from home and work) and creative workspaces (co-working spaces, makerspaces, fab labs). Bricolages, improvisations and guided visits coexist within a set time and are linked together through the act of walking to, discussing while and sharing online.
It is in the context of this new form of research culture and knowledge production that the Laboratory on Computer-Mediated Communication (LabCMO in French) proposes an AoIR preconference workshop. LabCMO is a research and sociotechnical experimentation space gathering scholars (students and professors) from diverse disciplines and interests (participatory culture, social computing, civic engagement, free software and citizen science…) around the broadly defined field of computer-mediated communication.
Within the AoIR 2018 theme of Transnational Materialities, LabCMO proposes an immersive half-day walked afternoon event focusing on the study of third places whose mandates intersect art, technology, and emerging digital practices. Through walking and talking, our learning expedition will cut across many of Montreal’s iconic quarters, allowing the participants to follow the cultural and social evolution of the city, from the early immigrant neighborhoods to the technological and artistic centres that characterize it today. Our first stop will be Montreal’s original fab lab, échoFab, located in the heart of the Innovation District of Montreal, Griffintown. échoFab is a community-based digital workshop experimenting with various digital manufacturing approaches. Our second stop will bring us to NOMAD Nation, a creative co-working production studio situated by the railroad tracks of the Mile End District. Led by Moment Factory founder Jason Rodi, NOMAD Nation houses a creative community specializing in live streaming and digital broadcasts. Our expedition will end at a makerspace, Eastern Bloc, located in the heart of Montreal’s Little Italy. Eastern Bloc explores new modes of production centred on audience participation, technological democratization, and the utilization of urban space.
Learning expeditions are also meant to encourage natural knowledge production, and accordingly include an unstructured documenting feature that will flow out of the collective experience. Participants will be invited to share what they are experiencing, seeing and learning throughout the expedition. OWEE events are “happenings,” therefore social media will be used to document the event in real time. Participants will create “metatexts,” allowing other participants as well as viewers to share the experience in real time. These online traces will also allow all to revisit the day and the events afterward.
The core expedition team will be composed of Nina Duque and Rémi Toupin, respectively PhD candidates in Communication Studies and Science and Technology Studies at University of Quebec at Montreal (UQAM), along with the two LabCMO codirectors, Florence Millerand, full professor in Communication Studies at UQAM, and Guillaume Latzko-Toth, associate professor in Communication Studies at Laval University. A team of volunteer students will accompany the group to help curate the event. Attendance is limited to 15 participants and registration is mandatory. Please send your requests to info [at] labcmo [dot] ca with the subject header: Learning Expedition Registration.
PLEASE NOTE: This workshop is a long afternoon walk through Montréal. The actual distance covered is roughly 5 kilometres (3 miles). We will be alternating between walking and using public transportation (self-funded), so a good pair of walking shoes is recommended. There should be no accessibility issues other than being able to get around. All the places visited in our programme are wheelchair adapted as is most of Montreal’s public transportation system.
In recent years, the abundance of digital data available and the creation of new tools to conduct digital research has transformed media research. Scholars can now easily monitor media coverage about key topics and events, understand public opinion dynamics overtime, and map digital communication networks. However, most of the data and tools available are proprietary and designed for commercial purposes. This workshop highlights the importance of open tools designed for academic and non-commercial researchers, and provides them with the opportunity to learn and use Media Cloud’s open source digital media analytics tools.
Media Cloud, a global archive of more than 760 million news stories – collecting content from 60,000 digital publications daily – is an open source platform developed by Harvard’s Berkman Klein Center for Internet and Society and MIT Media Lab’s Center for Civic Media. It currently supports three main tools:
-Explorer: A tool for querying the database, generate visualizations, and analize attention overtime, language, and geographies.
-Topics: A tool for sophisticated influence and language analyses that crawls the web to find all relevant content produce hyperlink and language maps.
-Sources: A tool to manage and understand news sources and collections in the database.
Originally created to evaluate the media’s framing of issues online and to map the information source networks publishing about particular topics, Media Cloud tools are now being used to answer research questions about: how information travels through media networks overtime, which sources are considered to be information authorities and influencers, what is the language used to cover an issue, and how media narratives evolve overtime.
This workshop may be of interest to researchers in the field of media representation and news analysis, digital journalism researchers, and anyone interested in learning more about new metrics for understanding media influence and impact. Media Cloud’s open source tools combine text analytics, entity detection, topic modelling, and network analysis. Researchers are also able to access our data through the public API.
The workshop will consist of four parts:
1. An introduction to digital news media analysis, and the importance of media analytics tools that are open source and available to any interested researcher
2. An introduction to Media Cloud tools, with an overview of our research methodology, the metrics we use, and demonstrations of the capabilities of Media Cloud tools
3. Group collaboration towards the development of relevant research questions that can be explored using Media Cloud tools
4. Guided use of Media Cloud tools to begin answering those research questions
Workshop participants will leave the session with skills needed to examine the Media Cloud source collections, to develop relevant and meaningful queries using the Media Cloud Explorer tool, and to begin running their own experiments using the Topic Mapper tools.
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Andrea L. Guzman, Anja Bechmann, Jaime Banks, Autumn Edwards, Chad Edwards, Steve Jones, Christoph Lutz, and Seth Lewis
As AoIR was taking shape nearly two decades ago, many of the emerging areas of research clustered around people’s interactions with one another online: how people communicated through the computer; how people formed communities in cyberspace; how people saw themselves through their virtual representations. Many of these core questions regarding new technologies have not changed even as technology has: We still want to know about people’s interactions with one another, the communities they form, and the self they perform. A key part in this research then and now has been the materiality of technology: its affordances, its biases, its (infra)structures, but also its status as human constructed and constantly evolving.
However, within the past few years a significant shift has been taking place within AoIR and across the many fields represented here. Scholars are no longer only interested in how people communicate through technology; they are increasingly taking up questions of how people interact with technology, specifically devices and applications designed to be social and intelligent: algorithms, artificial intelligence, socialbots, robots, and other related technologies. When McLuhan (1994) famously stated that the “medium is the message,” he was making a statement as to the importance of the materiality of the medium. But the medium that McLuhan envisioned was one that carried messages between and among people.
What does it mean for scholars of technology that the medium is now the message and messenger? How do we unfold layers of ontologies in the technologies and how do we account for them? How do we shift our focus from studying interactions through technology to with technology? How do we study the individual, social, and cultural implications of emerging technologies that are made to look and act more-and-more human? What theories do we draw upon to inform our research when so much of our scholarship, even that focused directly on the medium, evolved in a world where humans exclusively communicated? What methodologies are suitable to empirically investigate this shift? What does the future of AoIR look like as research in these areas increase? These are just some of the questions driving this half-day preconference in human-machine communication, or HMC. HMC is an area of communication research focused on people’s direct interactions with technology and the implications thereof. Within HMC the technology is theorized as more than a medium: it is a distinct entity either by design or in the mind of those interacting with it. Scholars of other closely related disciplinary, theoretical, or methodological backgrounds also share an interest in answering these questions.
The workshop will begin with a series of lightning talks by select HMC scholars on the questions driving their research and questions still to be answered. Next, participants will be divided into groups based on their area of interest (e.g., algorithms, chatbots, next generation internet infrastructures, social robots, automated journalism, AI as well as related issues, such as ethics or privacy) so that they can discuss shared aspects of their research. Finally, the entire group will discuss the overarching questions that served as the foundation for this workshop along with any emerging questions that arise during the breakout sessions.
Sponsors: EU Next Generation Internet (www.ngi.eu); the Communication and Social Robotics Labs, (www.combotlab.org); Shirley Papé Chair in Emerging Media, School of Journalism and Communication, University of Oregon.
Annette N Markham, Katrin Tildenberg, Gabriel Pereira, Elyzabeth Holford, Morna O’Connor, Ann Light, Elizabeth Whitney, Justin Lacko, Sarah Schorr, Ramona Dremljuga
Interested participants need to submit an expression of interest and intent to register for the conference before August 21, 2018, using this google form: https://goo.gl/forms/ch5mBZtluDkchuzp1 Pre-registration will enable participants to have access to our planning materials and have some prior knowledge of our plan for the exhibition. Late registration may be available Limit: 20 registrations [note, if you previously expressed interest, the system failed and you need to re-register using the form link above. If you have any problems or questions, contact firstname.lastname@example.org]
This workshop is the first of a two-part event at the conference that showcases a social research experiment called “Museum of Random Memory” (MoRM). MoRM is an interactive exhibition performed by (in this case) a team of researchers, students, activists, artists, computer scientists, and other “uncurators.” MoRM exemplifies the meeting point of digital and material culture with a particular focus on activism through critical pedagogy.
MoRM facilitates media, data, and digital literacy by engaging citizens about the topic of memory in the digital era. The exhibition/intervention itself can be large or small, in museums, libraries, classrooms, or festivals. On the surface, the interactive event is a playful engagement where visitors are encouraged to donate memories to the museum’s collection and view their memories alongside other donations. Below the surface, MoRM generates critical consciousness about multiple aspects of datafication, data collection, management and storage, big data, and corporate colonization of our personal data and memories through the seamlessness of apps and platforms on our digital devices. It engages participants in a form of collaborative future-making, linking creative practice to issues of temporality.
At this full-day workshop, we introduce MoRM as an arts-based public effort for critical data literacy; discuss the pedagogical and conceptual underpinnings of MoRM, and describe how previous exhibitions were conducted (Museum of Design in Barcelona; Aarhus Festival of Research in Denmark; Counterplay Festival in Aarhus, Denmark, Il Berneto in Orvieto, Italy; Data Justice Conference in Cardiff, Wales and Cork, Ireland). We will invite the workshop participants to be “uncurators” with us at the MoRM exhibition, which will be held later in the conference. The last stage of the preconference workshop will be to visit the exhibition site and brainstorm additional possibilities for collaborating with exhibition viewers.
MoRM is driven by the ambition to reach beyond the academy as activists and public educators. The theoretical foundations of MoRM have been inspired by a confluence of multiple disciplines/areas of study, including critical pedagogy/popular education (e.g. Paulo Freire); media literacy (e.g. Sonia Livingstone); theories of affordances (e.g., Anne Helmond, Taina Bucher); articulation and assemblages (e.g., Jennifer Slack & Greg Wise); and platform infrastructures (e.g., Jose van Dijck). The point of MoRM is not to collect empirical data about digital culture but to disseminate the findings of the past twenty years of internet research, promoting data literacy among the public.
About the interactive exhibition itself: MoRM is targeted to a general audience. Using many different visual displays, verbal prompts, and the lure of ‘something is happening here,’ we engage citizens/visitors in conversation about how the use of digital media platforms and technologies impacts the shape of our future memories and cultural heritages.
The focus on ‘memory’ allows us to engage people in thinking about larger and more complex sociotechnical relations. The idea of ‘random memory’ gives visitors an easy access point, since the phrase is playful and sparks curiosity. As we draw visitors further into the exhibition, we get them to explore their devices to find a memory to donate. As they do so, we engage them in conversation and probe the permanence/impermanence of their digital lives as part of a digitally-connected societal macro-layer.
The exact way that MoRM operates depends on location, scale, and target group. AoIR provides an opportunity to work through questions such as: What is the process of remembering and forgetting in the digital age? How are memories archived for us by digital platforms like Facebook and Google? Could we be more critical and conscious of how our future heritage is being created, not only by us but by many automated features of new tech? Eighty years from now, what will archaeologists find to teach them about what happened back in 2018? What would we like them to find? How can we use everyday memory-making practices to consider possible socio-technical futures?
Fabrizio Poltronieri, and Max Hänska
With contemporary online communications increasingly generating large volumes of visual data, scholars face the challenge of retrieving, wrangling, and analysing visual social media content at scale. Indeed, visual social media is attracting increasing attention in the field (Highfield & Leaver, 2016; Svensson & Russmann, 2017). While ‘big data’ techniques for analysing textual content (e.g. topic modelling) are already wide-spread, and quite advanced, similar techniques for analysing visual social media content (e.g. memes, images, videos) are nascent, and have not yet been widely deployed. How can we analyse visual social media content, given that the sheer volume of visual material requiring our consideration vastly exceed the strictures manual analysis impose on the amount of material that can realistically be analysed? This workshop offers an introduction and overview to available deep learning techniques for automating visual analysis, an introduction to tools for retrieving social media images, and the opportunity to plan an image retrieval, processing, and analysis pipeline. The workshop will focus on the following:
Tools and techniques for image retrieval, ingestion, and processing:
The workshop will introduce participants to the parameters of the Twitter, Instagram, and Flickr APIs for image collection and retrieval. The workshop will also introduce online tools and software packages for retrieving images from these various APIs, including Echosec (https://www.echosec.net), Netlytic (https://netlytic.org), Nvivo, and Boston University BU-TCAT.
Deep Learning techniques for image classification:
The workshop will Introduce the basic principles of using machine learning algorithms to train Convolutional Neural Networks (CNN) for image classification, the requirement of training data sets (including recommended parameters for the training data), and machine learning libraries (e.g. TensorFlow and Nvidia Digits). These techniques are particularly useful for researchers who want to train their own neural network to perform basic image classifications at scale, who have specific classification needs, and who have access to appropriate training data.
Cloud-based visual analysis tools:
Researchers who want to avoid training their own Neural Network, and require standard descriptions of visual material (including images and videos) can also rely on a set of cloud-based computer-vision toolkits for image analysis. These typically perform, inter alia, object recognition (does visual material depict people or animals, men or women, does it contain obscenities, etc.). The advantage of these services is that they generally offer much greater level of granularity than can be achieved through a self-trained CNN, though they are mostly not designed for highly specific classification needs. We will focus in particular on the operation, and output of following APIs: Amazon Rekognition, Google Vision, IBM Vision Recognition, and Microsoft Azure.
The workshop will consist of an introduction and overview of available techniques, and hands-on play with automatic visual analysis techniques. By the end of the workshop each participant will have sketched a research design that utilises automated image analysis. Participants should bring a laptop and a sample of images they wish to analyse.