Today I am again at the Association of Internet Researchers AoIR 2016 Conference in Berlin. Yesterday we had workshops, today the conference kicks off properly. Follow the tweets at: #aoir2016.
As usual this is a liveblog so all comments and corrections are very much welcomed.
PA-02 Platform Studies: The Rules of Engagement (Chair: Jean Burgess, QUT)
How affordances arise through relations between platforms, their different types of users, and what they do to the technology – Taina Bucher (University of Copenhagen) and Anne Helmond (University of Amsterdam)
Taina: Hearts on Twitter: In 2015 Twitter moved from stars to hearts, changing the affordances of the platform. They stated that they wanted to make the platform more accessible to new users, but that impacted on existing users.
Today we are going to talk about conceptualising affordances. In it’s original meaning an affordance is conceived of as a relational property (Gibson). For Norman perceived affordances were more the concern – thinking about how objects can exhibit or constrain particular actions. Affordances are not just the visual clues or possibilities, but can be felt. Gaver talks about these technology affordances. There are also social affordances – talked about my many – mainly about how poor technological affordances have impact on societies. It is mainly about impact of technology and how it can contain and constrain sociality. And finally we have communicative affordances (Hutchby), how technological affordances impact on communities and communications of practices.
So, what about platform changes? If we think about design affordances, we can see that there are different ways to understand this. The official reason for the design was given as about the audience, affording sociality of community and practices.
Affordances continues to play an important role in media and social media research. They tend to be conceptualised as either high-level or low-level affordances, with ontological and epistemological differences:
- High: affordance in the relation – actions enabled or constrained
- Low: affordance in the technical features of the user interface – reference to Gibson but they vary in where and when affordances are seen, and what features are supposed to enable or constrain.
Anne: We want to now turn to platform-sensitive approach, expanding the notion of the user –> different types of platform users, end-users, developers, researchers and advertisers – there is a real diversity of users and user needs and experiences here (see Gillespie on platforms. So, in the case of Twitter there are many users and many agendas – and multiple interfaces. Platforms are dynamic environments – and that differentiates social media platforms from Gibson’s environmental platforms. Computational systems driving media platforms are different, social media platforms adjust interfaces to their users through personalisation, A/B testing, algorithmically organised (e.g. Twitter recommending people to follow based on interests and actions).
In order to take a relational view of affordances, and do that justice, we also need to understand what users afford to the platforms – as they contribute, create content, provide data that enables to use and development and income (through advertisers) for the platform. Returning to Twitter… The platform affords different things for different people
Taking medium-specificity of platforms into account we can revisit earlier conceptions of affordance and critically analyse how they may be employed or translated to platform environments. Platform users are diverse and multiple, and relationships are multidirectional, with users contributing back to the platform. And those different users have different agendas around affordances – and in our Twitter case study, for instance, that includes developers and advertisers, users who are interested in affordances to measure user engagement.
How the social media APIs that scholars so often use for research are—for commercial reasons—skewed positively toward ‘connection’ and thus make it difficult to understand practices of ‘disconnection’ – Nicolas John (Hebrew University of Israel) and Asaf Nissenbaum (Hebrew University of Israel)
Consider this… On Facebook…If you add someone as a friend they are notified. If you unfriend them, they do not. If you post something you see it in your feed, if you delete it it is not broadcast. They have a page called World of Friends – they don’t have one called World of Enemies. And Facebook does not take kindly to app creators who seek to surface unfriending and removal of content. And Facebook is, like other social media platforms, therefore significantly biased towards positive friending and sharing actions. And that has implications for norms and for our research in these spaces.
One of our key questions here is what can’t we know about
Agnotology is defined as the study of ignorance. Robert Proctor talks about this in three terms: native state – childhood for instance; strategic ploy – e.g. the tobacco industry on health for years; lost realm – the knowledge that we cease to hold, that we loose.
I won’t go into detail on critiques of APIs for social science research, but as an overview the main critiques are:
- APIs are restrictive – they can cost money, we are limited to a percentage of the whole – Burgess and Bruns 2015; Bucher 2013; Bruns 2013; Driscoll and Walker
- APIs are opaque
- APIs can change with little notice (and do)
- Omitted data – Baym 2013 – now our point is that these platforms collect this data but do not share it.
- Bias to present – boyd and Crawford 2012
Asaf: Our methodology was to look at some of the most popular social media spaces and their APIs. We were were looking at connectivity in these spaces – liking, sharing, etc. And we also looked for the opposite traits – unliking, deletion, etc. We found that social media had very little data, if any, on “negative” traits – and we’ll look at this across three areas: other people and their content; me and my content; commercial users and their crowds.
Other people and their content – APIs tend to supply basic connectivity – friends/following, grouping, likes. Almost no historical content – except Facebook which shares when a user has liked a page. Current state only – disconnections are not accounted for. There is a reason to not know this data – privacy concerns perhaps – but that doesn’t explain my not being able to find this sort of information about my own profile.
Me and my content – negative traits and actions are hidden even from ourselves. Success is measured – likes and sharin, of you or by you. Decline is not – disconnections are lost connections… except on Twitter where you can see analytics of followers – but no names there, and not in the API. So we are losing who we once were but are not anymore. Social network sites do not see fit to share information over time… Lacking disconnection data is an idealogical and commercial issue.
Commercial users and their crowds – these users can see much more of their histories, and the negative actions online. They have a different regime of access in many cases, with the ups and downs revealed – though you may need to pay for access. Negative feedback receives special attention. Facebook offers the most detailed information on usage – including blocking and unliking information. Customers know more than users, or Pages vs. Groups.
Nicholas: So, implications. From what Asaf has shared shows the risk for API-based research… Where researchers’ work may be shaped by the affordances of the API being used. Any attempt to capture negative actions – unlikes, choices to leave or unfriend. If we can’t use APIs to measure social media phenomena, we have to use other means. So, unfriending is understood through surveys – time consuming and problematic. And that can put you off exploring these spaces – it limits research. The advertiser-friends user experience distorts the space – it’s like the stock market only reporting the rises except for a few super wealthy users who get the full picture.
A biography of Twitter (a story told through the intertwined stories of its key features and the social norms that give them meaning, drawing on archival material and oral history interviews with users) – Jean Burgess (Queensland University of Technology) and Nancy Baym (Microsoft Research)
The Bot Affair: Ashley Madison and Algorithmic Identities as Cultural Techniques – Tero Karppi, University at Buffalo, USA
As of 2012 Ashley Madison is the biggest online dating site targeted at those already in a committed relationship. Users are asked to share their gender, their sexuality, and to share images. Some aspects are free but message and image exchange are limited to paid accounts.
The site was hacked in 2016, stealing site user data which was then shared. Security experts who analysed the data assessed it as real, associated with real payment details etc. The hacker intention was to expose cheaters but my paper is focused on a different aspect of the aftermath. Analysis showed 43 male bots, and 70k female bots and that is the focus of my paper. And I want to think about this space and connectivity by removing the human user from the equation.
The method for me was about thinking about the distinction between human and non-human user, the individual and the bot. Eminating from germination theory I wanted to use cultural techniques – with materials, symbolic values, rules and places. So I am seeking elements of difference of different materials in the context of the hack and the aftermath.
So, looking at a news items: “Ashley madison, the dating website for cheaters, has admitted that some women on its site were virtual computer programmes instead of real women.” (CNN money), which goes onto say that users thought that they were cheating, but they weren’t after all! These bots interacted with users in a variety of ways from “winking” to messaging, etc. The role of the bot is to engage users in the platform and transform them into paying customers. A blogger talked about the space as all fake – the men are cheaters, the women are bots and only the credit card payments are real!
The fact that the bots are so gender imbalanced tells us the difference in how the platform imagines male and female users. In another commentary they comment on the ways in which fake accounts drew men in – both by implying real women were on the site, and by using real images on fake accounts… The lines between what is real and what is fake have been blurred. Commentators noted the opaqueness of connectivity here, and of the role of the bots. Who knows how many of the 4 million users were real?
The bots are designed to engage users, to appear as human to the extent that we understand human appearance. Santine Olympo talked about bots whilst others looking at algorithmic spaces and what can be imagined and created from our wants and needed. According to Ashley Madison employees the bots – or “angels” – were created to match the needs of users, recycling old images from real user accounts. This case brings together the “angel” and human users. A quote from a commentator imagines this as a science fiction fantasy where real women are replaced by perfect interested bots. We want authenticity in social media sites but bots are part of our mundane everyday existence and part of these spaces.
I want to finish by quoting from Ashley Madison’s terms and conditions, in which users agree that “some of the accounts and users you may encounter on the site may be fiction”.
Facebook algorithm ruins friendship – Taina Bucher, University of Copenhagen
“Rachel”, a Facebook user/informant states this in a tweet. She has a Facebook account that she doesn’t use much. She posts something and old school friends she has forgotten comment on it. She feels out of control… And what I want to focus on today are ordinary affects of algorithmic life taking that idea from ?’s work and Catherine Stewart’s approach to using this in the context of understanding the encounters between people and algorithmic processes. I want to think about the encounter and how the encounter itself becoming generative.
I think that the fetish could be one place to start in knowing algorithms… And how people become attuned to them. We don’t want to treat algorithms as a fetish. The fetishist doesn’t care about the object, just about how the object makes them feel. And so the algorithm as fetish can be a mood maker, using the “power of engagement”. The power does not reside in the algorithm, but in the types of ways people imagine the algorithm to exist and impact upon them.
So, I have undertaken a study of people’s personal algorithm stories, looking at people’s personal algorithm stories about Facebook algorithm; monitoring and querying Twitter for comments and stories (through keywords) relating to Facebook algorithms. And a total of 25 interviews were undertaken via email, chat and Skype.
So, when Rachel tweeted about Facebook and friendship, that gave me the starting point to understand stories and the context for these positions through interviews. And what repeatedly arose was the uncanny nature of Facebook algorithms. Take, for instance Micheal, a musician in LA. He shares a post and usually the likes come in rapidly, but this time nothing… He tweets that the algorithm is “super frustrating” and he believes that Facebook only shows paid for posts. Like others he has developed his own strategy to show posts more clearly. He says:
“If the status doesn’t build buzz (likes, comments, shares) within the first 10 minutes or so it immediately starts moving down the news feed and eventually gets lost.”
Adapting behaviour to social media platforms and their operation can be seen as a form of “optimisation”. Users aren’t just updating their profile or hoping to be seen, they are trying to change behaviours to be better seen by the algorithm. And this takes us to the algorithmic imaginary, the ways of thinking about what algorithms are, what they should be, how they function, and what these imaginations in turn make possible. Many of our participants talked about changing behaviours for the platform. Rachel talks about “clicking every day to change what will show up on her feed” is not only her using the platform, but thinking and behaving differently in the space. Adverts can also suggest algorithmic intervention and, no matter whether the user is profiled or not (e.g. for anti-wrinkle cream), users can feel profiled regardless.
So, people do things to algorithms – disrupting liking practices, comment more frequently to increase visibility, emphasise positively charged words, etc. these are not just interpreted by the algorithm but also shape that algorithm. Critiquing the algorithm is not enough, people are also part of the algorithm and impact upon its function.
Algorithmic identity – Michael Stevenson, University of Groningen, Netherlands
Michael is starting with a poster of Blade Runner… Algorithmic identity brings to mind cyberpunk and science fiction. But day to day algorithmic identity is often about ads for houses, credit scores… And I’m interested in this connection between this clash of technological cool vs mundane instruments of capitalism.
For critics the “cool” is seen as an ideological cover for the underlying political economy. We can look at the rhetoric around technology – “rupture talk”, digital utopianism as that covering of business models etc. Evgeny Morozov writes entertainingly of this issue. I think this critique is useful but I also think that it can be too easy… We’ve seen Morozov tear into Jeff Jarvis and Tim O’Reilly, describing the latter as a spin doctor for Silicon Valley. I think that’s too easy…
My response is this… An image of Christopher Walken saying “needs more Bourdieu”. I think we need to take seriously the values and cultures and the effort it takes to create those. Bourdieu talks about the new media field with areas of “web native”, open, participatory, transparant at one end of the spectrum – the “autonomous pole”; and the “heteronomous pole” of mass/traditional media, closed, controlled, opaque. The idea is that actors locate themselves between these poles… There is also competition to be seen as the most open, the most participatory – you may remember a post from a few years back on Google’s idea of open versus that of Facebook. Bourdieu talks of the autonomous pole as being about downplaying income and economic value, whereas the heteronomous pole is much more directly about that…
So, I am looking at “Everything” – a site designed in the 1990s. It was built by the guys behind Slashdot. It was intended as a compendium of knowledge to support that site and accompany it – items of common interest, background knowledge that wasn’t news. If we look at the site we see implicit and explicit forms of impact… Voting forms on articles (e.g. “I like this write up”), and soft links at the bottom of the page – generated by these types of feedback and engagement. This was the first version in the 1990s. Then in 1999 Nathan Dussendorf(?) developed the Everything2 built with the Everything Development Engine. This is still online. Here you see that techniques of algorithmic identity and datafication of users, this is very explicitly presented – very much unlike Facebook. Among the geeks here the technology is put on top, showing reputation on the site. And being open source, if you wanted to understand the recommendation engine you could just look it up.
If we think of algorithms as talk makers, and we look back at 1999 Everything2, you see the tracking and datafication in place but the statement around it talks about web 2.0/social media type ideas of democracy, meritocracy, conflations of cultural values and social actions with technologies and techniques. Aspects of this are bottom up and you also talk about the role of cookies, and the addressing of privacy. And it directly says “the more you participate, the greater the opportunity for you to mold it your way”.
Thinking about Field Theory we can see some symbolic exclusion – of Microsoft, of large organisations – as a way to position Everything2 within the field. This continues throughout the documentation across the site. And within this field “making money is not a sin” – that developers want to do cool stuff, but that can sit alongside making money.
So, I don’t want to suggest this is a utopian space… Everything2 had a business model, but this was of its time for open source software. The idea was to demonstrate capabilities of the development framework, to get them to use it, and to then get them to pay for services… But this was 2001 and the bubble burst… So the developers turned to “real jobs”. But Everything2 is still out there… And you can play with the first version on an archived version if you are curious!
The Algorithmic Listener – Robert Prey, University of Groningen, Netherlands
This is a version of a paper I am working on – feedback appreciated. And this was sparked by re-reading Raymond Williams, who talks about “there are in fact no masses, but only ways of seeing people as masses” (1958/2011). But I think that in the current environment Williams might now say “there are in fact no individuals, but only ways of seeing people as individuals”. and for me I’m looking at this through the lens of music platforms.
In an increasingly crowded and competitive sector platforms like Spotify, SoundCloud, Apple Music, Deezer, Pandora, Tidel, those platforms are increasingly trying to differentiate themselves through recommendation engines. And I’ll go on to talk about recommendations as individualisation.
Pandora internet radio calls itself the “music genome project” and sees music as genes. It seeks to provide recommendatoins that are outside the distorting impact of cultural information, e.g. you might like “The colour of my love” but you might be put off by the fact that Celine Dion is not cool. They market themselves against the crowd. They play on the individual as the part separated from the whole. However…
Many of you will be familiar with Spotify, and will therefore be familiar with Discover Weekly. The core of Spotify is the “taste profile”. Every interaction you have is captured and recorded in real time – selected artists, songs, behaviours, what you listen to and for how long, what you skip. Discover weekly uses both the taste profile and aspects of collaborative filtering – selecting songs you haven’t discovered that fits your taste profile. So whilst it builds a unique identity for each user, it also relies heavily on other peoples’ taste. Pandora treats other people as distortion, Spotify sees it as more information. Discover weekly does also understands the user based on current and previous behaviours. Ajay Kalia (Spotify) says:
“We believe that it’s important to recognise that a single music listener is usually many listeners… [A] person’s preference will vary by the type of music, by their current activity, by the time of day, and so on. Our goal then is to come up with the right recommendation…”
This treats identity as being in context, as being the sum of our contexts. Previously fixed categories, like gender, are not assigned at the beginning but emerge from behaviours and data. Pagano talks about this, whilst Cheney-Lippold (2011) talks about “cybernetic relationship to individual” and the idea of individuation (Simondon). For Simondon we are not individuals, individuals are an effect of individuation, not the cause. A focus on individuation transforms our relationship to recommendation systems… We shouldn’t be asking if they understand who we are, but the extent to which the person is an effect of personalisation. Personalisation is seen as about you and your need. From a Simondonian perspective there is no “you” or “want” outside of technology. In taking this perspective we have to acknowledge the political economy of music streaming systems…
And the reality is that streaming services are increasingly important to industry and advertisers, particularly as many users use the free variants. And a developer of Pandora talks about the importance for understanding profiles for advertisers. Pandora boasts that they have 700 audience segments to data. “Whether you want to reach fitness-driven moms in Atlanta or mobile Gen X-er… “. The Echo Nest, now owned by Spotify, had created highly detailed consumer profiling before it was brought up. That idea isn’t new, but the detail is. The range of segments here is highly granular… And this brings us to the point that we need to take seriously what Nick Seaver (2015) says we need to think of: “contextualisation as a practice in its own right”.
This matters as the categories that emerge online have profound impacts on how we discover and encounter our world.
Q1) I think it’s about music category but also has wider relevance… I had an introduction to the NLP process of Topic Modelling – where you label categories after the factor… The machine sorts without those labels and takes it from the data. Do you have a sense of whether the categorisation is top down, or is it emerging from the data? And if there is similar top down or bottom up categorisation in the other presentations, that would be interesting.
A1 – Robert) I think that’s an interesting question. Many segments are impacted by advertisers, and identifying groups they want to reach… But they may also
Micheal) You talked about the Ashley Madison bots – did they have categorisation, A/B testing, etc. to find successful bots?
Tero) I don’t know but I think looking at how machine learning and machine learning history
Micheal) The idea of content filtering from the bottom to the top was part of the thinking behind Everything…
Q2) I wanted to ask about the feedback loop between the platforms and the users, who are implicated here, in formation of categories and shaping platforms.
A2 – Taina) Not so much in the work I showed but I have had some in-depth Skype interviews with school children, and they all had awareness of some of these (Facebook algorithm) issues, press coverage and particularly the review of the year type videos… People pick up on this, and the power of the algorithm. One of the participants emails me since the study noting how much she sees writing about the algorithm, and about algorithms in other spaces. Awareness is growing much more about the algorithms shaping spaces. It is more prominent than it was.
Q3) I wanted to ask Michael about that idea of positioning Everything2 in relation to other sites… And also the idea of the individual being transformed by platforms like Spotify…
A3 – Michael) I guess the Bourdieun vision is that anyone who wants to position themselves on the spectrum, they can. With Everything you had this moment during the Internet Bubble, a form of utopianism… You see it come together somewhat… And the gap between Wired – traditional mass media – and smaller players but then also a coming together around shared interests and common enemies.
A3 – Robert) There were segments that did come from media, from radio and for advertisers and that’s where the idea of genre came in… That has real effects… When I was at High School there were common groups around particular genres… But right now the move to streaming and online music means there are far more mixed listening and people self-organise in different ways. There has been de-bunking of Bourdieu, but his work was at a really different time.
Q4) I wanted to ask about interactions between humans and non-human. Taina, did people feel positive impacts of understanding Facebook algorithms… Or did you see frustrations with the Twitter algorithms. And Tero, I was wondering how those bots had been shaped by humans.
A4 – Taina) The human and non-human, and whether people felt more or less frustrated by understanding the algorithm. Even if they felt they knew, it changes all the time, their strategies might help but then become obsolete… And practices of concealment and misinformation were tactics here. But just knowing what is taking place, and trying to figure it out, is something that I get a sense is helpful… But maybe that is’t the right answer to it. And that notion of a human and a non human is interesting, particularly for when we see something as human, and when we see things as non-human. In terms of some of the controversies… When is an algorithm blamed versus a human… Well there is no necessary link/consistency there… So when do we assign humanness and non-humanness to the system and does it make a difference?
A4 – Tero) I think that’s a really interesting questions…. Looking at social media now from this perspective helps us to understand that, and the idea of how we understand what is human and what is non-human agency… And what it is to be a human.
Q5) I’m afraid I couldn’t here this question
A5 – Richard) Spotify supports what Deleuze wrote about in terms of the individual and how aspects of our personality are highlighted at the points that is convenient. And how does that effect help us regulate. Maybe the individual isn’t the most appropriate unit any more?
A5 – Taine) For users the exposure that they are being manipulated or can be summed up by the algorithm, that is what can upset or disconcert them… They don’t like to feel summed up by that…
Q6) I really like the idea of the imagined… And perceptions of non-human actors… In the Ashley Madison case we assume that men thought bots were real… But maybe not everyone did that. I think that moment of how and when people imagine and ascribe human or non-human status here. In one way we aren’t concerned by the imaginary… And in another way we might need to consider different imaginaries – the imaginary of the platform creators vs. users for instance.
A6 – Tero) Right now I’m thinking about two imaginaries here… Ashley Madison’s imaginary around the bots, and the users encountering them and how they imagine those bots…
A6 – Taine) A good question… How many imaginaries o you think?! It is about understanding more who you encounter, who you engage with. Imaginaries are tied to how people conceive of their practice in their context, which varies widely, in terms of practices and what you might post…
PS-09: Privacy (Chair: Michael Zimmer)
Unconnected: How Privacy Concerns Impact Internet Adoption – Eszter Hargittai, Ashley Walker, University of Zurich
The literature in this area seems to target the usual suspects – age, socio-economic status… But the literature does not tend to talk about privacy. I think one of the reasons may be the idea that you can’t compare users and non-users of the internet on privacy. But we have located a data set that does address this issue.
The U.S. Federal Communication Commission’s issued a National Consumer’s Broadband Service Capability Service in 2009 – when about 24% of Americans were still not yet online. This work is some years ago but our insterest is in the comparison rather than numbers/percentages. And this questioned both internet users and non-users.
One of the questions was: “It is too easy for my personal information to be stolen online” and participants were asked if they Strongly agreed, somewhat agreed, somewhat disagreed, disagreed. We looked at that as bivariate – strongly agreed or not. And analysing that we found that among internet users 63.3% said they strongly agreed versus 81% of non internet users. Now we did analyse demographically… It is what you expect generally – more older people are not online (though interestingly more female respondents are online). But even then the internet non-users again strongly agreed about that privacy/concern question.
So, what does that mean? Well getting people online should address people’s concerns about privacy issues. There is also a methodological takeaway – there is value to asking non-users about internet-related questions – as they may explain their reasons.
Q1) Was it asked whether they had previously been online?
A1) There is data on drop outs, but I don’t know if that was captured here.
Q2) Is there a differentiation in how internet use is done – frequently or not?
A2) No, I think it was use or non-use. But we have a paper coming out on those with disabilities and detailed questions on internet skills and other factors – that is a strength of the dataset.
Q3) Are there security or privacy questions in the dataset?
A3) I don’t think there are, or we would have used them. It’s a big national dataset… There is a lot on type of internet connection and quality of access in there, if that is of interest.
Note, there is more on some of the issues around access, motivations and skills in the Royal Society of Edinburgh Spreading the Benefits of Digital Participation in Scotland Inquiry report (Fourman et al 2014). I was a member of this inquiry so if anyone at AoIR2016 is interested in finding out more, let me know.
Enhancing online privacy at the user level: the role of internet skills and policy implications – Moritz Büchi, Natascha Just, Michael Latzer, U of Zurich, Switzerland
Natascha: This presentation is connected with a paper we just published and where you can read more if you are interested.
So, why do we care about privacy protection? Well there is increased interest in/availability of personal data. We see big data as a new asset class, we see new methods of value extraction, we see growth potential of data-driven management, and we see platformisation of internet-based markets. Users have to continually balance the benefits with the risks of disclosure. And we see issues of online privacy and digital inequality – those with fewer digital skills are more vulnerable to privacy risks.
We see governance becoming increasingly important and there is an issue of understanding appropriate measures. Market solutions by industry self-regulation is problematic because of a lack of incentives as they benefit from data. At the same time states are not well placed to regulate because of their knowledge and the dynamic nature of the tech sector. There is also a route through users’ self-help. Users self-help can be an effective method to protect privacy – whether opting out, or using privacy enhancing technology. But we are increasingly concerned but we still share our data and engage in behaviour that could threaten our privacy online. And understanding that is crucial to understand what can trigger users towards self-help behaviour. To do that we need evidence, and we have been collecting that through a world internet study.
Moritz: We can imperically address issues of attitudes, concerns and skills. The literature finds these all as important, but usually at most two factors covered in the literature. Our research design and contributions look at general population data, nationally representative so that they can feed into policy. The data was collected in the World Internet Project, though many questions only asked in Switzerland. Participants were approached on landline and mobile phones. And our participants had about 88% internet users – that maps to the approx. population using the internet in Switzerland.
We found a positive effect of privacy attitudes on behaviours – but a small effect. There was a strong effect of privacy breaches and engaging in privacy protection behaviours. And general internet skills also had an effect on privacy protection. Privacy breaches – learning the hard way – do predict privacy self-protection. Caring is not enough – that pro-privacy attitudes do not really predict privacy protection behaviours. But skills are central – and that can mean that digital inequalities may be exacerbated because users with low general internet skills do not tend to engage in privacy protection behaviour.
Q1) What do you mean by internet skills?
A1 – Moritz): In this case there were questions that participants were asked, following a model by Alexander von Durnstern and colleagues developed, that asks for agreement or disagreement
Navigating between privacy settings and visibility rules: online self-disclosure in the social web – Manuela Farinosi1,Sakari Taipale2, 1: University of Udine; 2: University of Jyväskylä
Our work is focused on self-disclosure online, and particularly whether young people are concerned about privacy in relation to other internet users, privacy to Facebook, or privacy to others.
Facebook offers complex privacy settings allowing users to adopt a range of strategies in managing their information and sharing online. Waters and Ackerman (2011) talk about the practice of managing privacy settings and factors that play a role including culture, motivation, risk-taking ratio, etc. And other factors are at play here. Fuchs (2012) talks about Facebook as commercial organisation and concerns around that. But only some users are aware of the platform’s access to their data, may believe their content is (relatively) private. And for many users privacy to other people is more crucial than privacy to Facebook.
And there are differences in privacy management… Women are less likely to share their phone number, sexual orientation or book preferences. Men are more likely to share corporate information and political views. Several scholars have found that women are more cautious about sharing their information online. Nosko et al (2010) found no significant difference in information disclosure except for political informaltion (which men still do more of).
Sakari: Manuela conducted an online survey in 2012 in Italy with single and multiple choice questions. It was issued to university students – 1125 responses were collected. We focused on 18-38 year old respondents, and only those using facebook. We have slightly more female than male participants, mainly 18-25 years old. Mostly single (but not all). And most use facebook everyday.
So, a quick reminder of Facebook’s privacy settings… (a screenshot reminder, you’ve seen these if you’ve edited yours).
To the results… We found that the data that are most often kept private and not shared are mobile phone number, postal address or residence, and usernames of instant messaging services. The only data they do share is email address. But disclosure is high of other types of data – birth date for instance. And they were not using friends list to manage data. Our research also confirmed that women are more cautious about sharing their data, and men are more likely to share political views. The only not gender related issues were disclosure of email and date of birth.
Concerns were mainly about other users, rather than Facebook, but it was not substantially different in Italy. We found very consistent gender effects across our study. We also checked factors related to concerns but age, marital status, education, and perceived level of expertise as Facebook user did not have a significant impact. The more time you spend on Facebook, the less likely you are to care about privacy issues. There was also a connection between respondents’ privacy concerns were related to disclosures by others on their wall.
So, conclusions, women are more aware of online privacy protection than men, and protection of private sphere. They take more active self protection there. And we speculate on the reasons… There are practices around sense of security/insecurity, risk perception between men and women, and the more sociological understanding of women as maintainers of social labour – used to taking more care of their material… Future research needed though.
Q1) When you asked users about privacy settings on Facebook how did you ask that?
A1) They could go and check, or they could remember.
WHOSE PRIVACY? LOBBYING FOR THE FREE FLOW OF EUROPEAN PERSONAL DATA – Jockum Philip Hildén, University of Helsinki, Finland
My focus is related to political science… And my topic is lobbying for the free flow of European Personal Data – and how the General Data Protection Regulation come into being and which lobbyists influenced the legislators. This is a new piece of regulation coming in next year. It was the subject of a great deal of lobbying – it became visible when the regulation was in parliament, but the lobbying was much earlier than that.
So, a quick description of EU law making. There is the European Commission which proposes legislation and that goes to both the Council of Europe and also to the Parliament. Both draw up regulations based on the proposal and then that becomes final regulation. In this particular case there was public consultation before the final regulation so I looked at a wide range of publicly available position pages. Looking across here I could see 10 types of stakeholders offering replies to the position papers – far more in 2011 than to the first version in 2009. Companies in the US participated to a very high degree – almost as much as those in the UK and France. That’s interesting… And that’s partly to do with the extended scope of this new regulation that covers EU but also service providers in the US and other locations. This idea is not exclusive to this regulation, known as “the Brussels effect”.
In terms of sector I have categorised the stakeholders so I have divided IP and Node communications for instance, to understand their interests. But I am interested in what they are saying, so I draw on Kluver (2013) and the “preference attainment model” to compare policy preferences of interest groups with the Commissions preliminary draft proposal, the Commission’s final proposal, and the final legislative act adopted by the council. So, what interests did the council take into account? Well almost every article changed – which makes those changes hard to pin down. But…
There is an EU Power Struggle. The Commission draft contained 26 different cases where it was empowered to adopt delegated acts. All but one of these articles were removed from the Council’s draft. And there were 48 exceptions for member states, most of them are “in the public interest”… But that could mean anything! And thus the role of nation states comes into question. The idea of European law is to have consistent policy – that amount of variance undermines that.
We also see a degree of User disempowerment. Here we see responses from Digital Europe – a group of organisations doing any sort of surveillance; But we also see the American Chambers of Commerce submitting responses. In these responses both are lobbying for “implicit consent” – the original draft requested explicit consent. And the Commission sort of brought into this, using a concept of unambiguous consent… Which is itself very ambiguous. Looking at the Council vs Free Data Advocates and then compared to Council vs Privacy Advocates. The Free Data Advocates are pro free movement of data, and privacy – as that’s useful to them too, but they are not keen on greater Commission powers. Privacy Advocates are pro privacy and more supportive of Commission powers.
In Search of Safe Harbors – Privacy and Surveillance of Refugees in Europe – Paula Kift, New York University, United States of America
The Politics of Internet Research: Reflecting on the challenges and responsibilities of policy engagement
Victoria: I am Vicky Nash and I have convened a round table of members of the international network of internet research centres.
Juan-Carlos: I am director of the Nexa Center for Internet and Society in Italy and we are mainly computer scientists like myself, and lawers. We are ten years old.
Wolfgang: I am associated with two centres, in Humboldt primarily and our interest is in governance and surveillance primarily. We are celebrating our five birthday this year. I also work with the Hans-Bredow-Institut a traditional media institute, multidisciplinary, and we increasingly focus on the internet and internet studies as part of our work.
Bianca: I am representing Bill Dutton. I am Assistant Director of the Quello Center at Michigan State University centre. We were more focused on traditional media but have moved towards internet policy in the last few years as Bill moved to join us. There are three of us right now, but we are currently recruiting for a policy post-doc.
Victoria: Thanks for that, I should talk about the department I am representing… We are in a very traditional institution but our focus has explicitly always been involvement in policy and real world impact.
Victoria: So, over the last five or so years, it does feel like there are particular challenges arising now, especially working with politicians. And I was wondering if other types of researchers are facing those same challenges – is it about politics, or is it specific to internet studies. So, can I kick off and ask you to give me an example of a policy your centre has engaged in, how you were involved, and the experience of that.
Juan-Carlos: There are several examples. One with the regional government in our region of Italy. We were aware of data and participatory information issues in Europe. We reached out and asked if they were aware. We wanted to make them aware of opportunities to open up data, and build on OECD work, but we were also doing some research ourselves. Everybody agreed in the technical infrastructure and on political level… We assisted them in creating the first open data portal in Italy, and one of the first in Europe. And that was great, it was satisfying at the time. Nothing was controversial, we were following a path in Europe… But with a change of regional government that portal has somewhat been neglected so that is frustrating…
Victoria: What motivated that approach you made?
JC: We had a chance to do something new and exciting. We had the know-how and the way it could be, at least in Italy, and that seemed like a great opportunity.
Wolfgang: My centres, I’m kind of an outsider in political governance as I’m concerned with media. But in internet governance it feels like this is our space and we are invested in how it is governed – more so than in other areas. The example I have is from more traditional media work… And that’s from the Hans-Bredow-Institute. We were asked to investigate for a report on usage patterns changes, technology changes, and puts strain on governance structures in Germany… And where there is a need for solutions to make federal and state law in Germany more convergent and able to cope with those changes. But you have to be careful when providing options, because of course you can make some options more appealing than others… So you have to be clear about whether you will be and present it as neutral, or whether you prefer an option and present it differently. And that’s interesting and challenging as an academic and with the role of an academic and institution.
Victoria: So did you consciously present options you did not support?
Wolfgang: Yes, we did. And there were two reasons for this… They were convinced we would come up with a suggestion and basis to start working with… And they accepted that we would not be specifically taking a side – for the federal or local government. And also they were confident we wouldn’t attempt to mess up the system… We didn’t present the ideal but we understood other dependencies and factors and trusted us to only put in suggestions to enhance and practically work, not replace the whole thing…
Victoria: And did they use your options?
Wolfgang: They ignored some suggestions, but where they acted they did take our options.
Bianca: I’ll talk about a semi-successful project. We were looking at detailed postcode level data on internet access and quality and reasons for that. We submitted to the National Science Foundation, it was rejected, then two weeks later we were invited to an event on just that topic by the NPIA. So we are collectively drafting suggestions from the NPIA and from a wide range of many research centres, and we are drafting that now. It was nice to be invited by policy makers… and interesting to see that idea picked up through that process in some way…
Victoria: That’s maybe an unintended consequences aspect there… And that suggestion to work with others was right for you?
Bianca: We were already keen to work with other research centres but actually we also now have policy makers and other stakeholders around the table and that’s really useful.
Victoria: those were all very positive… Maybe you could reflect on more problematic examples…
JC: Ministers often want to show that they are consulting on policy but often that is a gesture, a political move to listen but then policy made an entirely different way… After a while you get used to that. And then you have to calculate whether you participate or not – there is a time aspect there.
Victoria: And for conflict of interest reasons you pay those costs of participating…
JC: Absolutely, the costs are on you.
Wolfgang: We have had contact from ministeries in Germany but then discovered they are interested in the process as a public relations tool rather than as a genuine interest in the outcome. So now we assess that interest and engage – or don’t – accordingly. We try to say at the beginning “no, please speak to someone else” when needed. At Humboldt is reluctant to engage in policy making, and that’s a historical thing, but people expect us to get involved. We are one of the few places that can deliver monitoring on the internet, and there is an expectation to do that… And when ministeries design new programmes, we are often asked to be engaged and we have learned to be cautious about when we engage. Experience helps but you see different ways to approach academia – can be PR, sometimes you want support for your position or support politically, or you can actually be engaged in research to learn and have expertise and information. If you can see what approach it is, you can handle it appropriately.
Victoria: I think as a general piece of advice – to always question “why am I being approached” in the framing of “what are their motivations?”, that is very useful.
Wolfgang: I think starting in terms of research questions and programmes that you are concerned with gives you a counterpoint in your own thinking to dealing with requests. Then when good opportunities come up you can take it and make use of it… But academic value can be limited of some approaches so you need a good reason to engage in those projects and they have to align with your own priorities.
Bianca: My bad example is related to that. The Net Neutrality debate is a big part of our work… There are a lot of partisan opinions on that, and not a lot of neutral research there. We wanted to do a big project there but when we try to get funding for that we have been steered to stay away. We’ve been steered that talking about policy with policy makers is very negative, it is taken poorly. This debate has been bouncing around for 10 years, we want to see where Net Neutrality is imposed if we see changes in investment… But we need funding to do that… And funders don’t want to do it and are usually very cosy with policy makers…
Victoria: This is absolutely an issue, these concerns are in the minds of policy makers as well and that’s important.
Wolfgang: When we talk about research in our field and policy makers, it’s not just about when policy makers approach you to do something… You have a term like Net Neutrality at the centre that requires you to be either neutral or not neutral, that really shapes how you handle that as an academic… You can become, without wanting it, someone promoting one side sometimes. On a minor protection issue we did some work on co-regulation with Australia that seemed to solve a problem… But then after this debate in Germany and started drafting the inter-state treaty on media regulation, the policy makers were interested… And then we felt that we should support it… and I entered the stage but it’s not my question anymore… So you have opinion about how you want something done…
JC: As a coordinator of a European project there was a call that included a topic of “Net Neutrality” – we made a proposal but what happened afterwards clearly proved that that whole area was topic. It was in the call… But we should have framed it differently. Again at European level you see the Commission funds research, you see the outcomes, and then they put out a call that entirely contradicts the work that they funded for political reasons. There is such a drive for evidence-based policy making that it is important that they frame that way… It is evidence-based when it fits their agenda, not when it doesn’t.
Victoria: I did some work with the Department of Media, Culture and Sport last year, again on minor protection, and we were told at the offset to assume porn caused harm to minors. And the frames of reference was shaped to be technical – about access etc. They did bring in a range of academic expertise but the terms of reference really constrained the contribution that was possible. So, there are real bear traps out there!
Wolfgang: A few years back the European Commission asked researchers to look at broadcasters and interruptions to broadcasts and the role of advertising, even though we need money we do not do that, it isn’t answering interesting research questions for us.
Victoria: I raised a question earlier about the specific stakes that academia has in the internet, it isn’t just what we study. Do you want to say more about that.
Wolfgang: Yes, at the pre-conference we had an STS stream… People said “of course we engage with policy” and I was wondering why that is the main position… But the internet comes from academia and there is a long standing tradition of engagement in policy making. Academics do engage with media policy, but they would’t class it as “our domain”, but they were not there are part of the beginning – academia was part of that beginning of the internet.
Q1) I wonder if you are mistaking the “of-ness” with the fact that the internet is still being formed, still in the making. Broadcast is established, the internet is in constant construction.
A1 – Wolfgang) I see that
Q1) I don’t know about Europe but in the US since the 1970s there have been deliberate efforts to reduce the power of decision makers and policy makers to work with researchers…
A1 – Bianca) The Federal Communications Commission is mainly made of economists…
Q1) Requirements and roles constrain activities. The assumption of evidence-based decisions is no longer there.
Q2) I think that there is also the issue of shifting governance. Internet governance is changing and so many academics are researching the governance of the internet, we reflect greatly on that. The internet and also the governance structure are still in the making.
Victoria: Do you feel like if you were sick of the process tomorrow, you’d still want to engage with policy making?
A2 – Phoebe) We are a publicly funded university and we are focused on digital inequalities… We feel real responsibility to get involved, to offer advice and opinions based on our advice. On other topics we’d feel less responsible, depending on the impact it would have. It is a public interest thing.
A2 – Wolfgang) When we look at our mission at the Hans-Bredow-Institute we have a vague and normative mission – we think a functioning public sphere is important for democracy… Our tradition is research into public spheres… We have a responsibility there. But we also have a responsibility that the evaluation of academic research becomes more and more important but there is no mechanism to ensure researchers answer the problems that society has… We have a completely divided set of research councils and their yardsticks are academic excellence. State broadcasters do research but with no peer review at all… There are some calls from the Ministry of Science that are problem-orientated but on the whole there isn’t that focus on social issues and relevance in the reward process, in the understanding of prestige.
Victoria: In the UK we have a bizarre dichotomy where research is measured against two measures: impact – where policy impact has real value – and that applies in all fields; but there is also regulation that you cannot use project funds to “lobby” government – which means you potentially cannot communicate research to politicians who disagree. This happened because a research organisation (not a university) opposed government policy with research funded by them… Implications for universities is currently uncleared.
JC: Italy is implementing a similar system to the UK. Often there is no actual mandate on a topic, so individuals come up with ideas without numbers and plans… We think there is a gap – but it is government and ministries work. We are funded to work in the national interest… But we need resources to help there. We are filling gaps in a way that is not sustainable in the long term really – you are evaluated on other criteria.
Q3) I wanted to ask about policy research… I was wondering if there is policy research we do not want to engage in. In Europe, and elsewhere, there is increasing need to attract research… What are the guidelines or principles around what we do or do not go for funding wise.
A3 – Bianca) We are small so we go for what interests us… But we have an advisory board that guides us.
A3 – Wolfgang) I’m not sure that there are overarching guidelines – there may be for other types of special centres – but it’s an interesting thing to have a more formalised exchange like we have right now…
A3 – JC) No, no blockers for us.
A3 – Victoria) Academic freedom is vigorously held up at Oxford but that can mean we have radically different research agendas in the same centre.
Q4) With that lack of guidance, isn’t there a need for academics to show that they have trust, especially in the public sphere, especially when getting funding from, say, Google or Microsoft. And how can you embed that trust?
A4 – Wolfgang) I think peer review as a system functions to support that trust. But we have to think about other institutional settings, and that there is enough oversight… And many associations, like Liebneiz, requires an institutional review board, to look over the research agenda and ensure some outside scrutiny. I wouldn’t say every organisation or research centre needs that – it can be helpful but costly in terms of time in particular. And you cannot trust the general public to do that, you need it to be peers. An interesting question though, especially as Humboldt has national funding from Google… In this network academics play a role, and organisations play a role, and you have to understand the networks and relationships of partners you work with, and their interests.