News, News, News

This blog has been terribly neglected in the last few months (apologies!) but I have some exciting news to share:

  • I received my doctorate from the University of St. Gallen in February 2016 and was fortunate enough to be one of the few graduates with “summa cum laude” (highest distinction).
  • As of January 2016 I started as an Assistant Professor at BI Norwegian School in Oslo, Department of Communication and Culture. In addition, I have an appointment as a researcher at the University of Leipzig, Institute of Communication and Media Studies.
  • Exciting times: At BI, together with a few colleagues from the department, we founded the Nordic Centre for Internet & Society and are planning to expand it gradually. Some news are on the site of the Centre, for example my visit of the ICA Conference, the EGOS Colloquium and the Social Media & Society Conference (including an award as “Most Engaged Attendee on Twitter 😉 and the publication of a paper about the sharing economy in Computers in Human Behavior.
  • Two of my co-authored papers were recently accepted. The first at the Journal of the Association for Information Science and Technology (JASIST) about serendipity, the second at Mobile Media & Communication about Tinder. They will be out shortly.
  • We managed to get an EU grant to investigate “Participation, Privacy and Power in the Sharing Economy” with a team of six universities in total and one company. More infos shortly!



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Twitter’s image problem

I often see people praising Twitter for its usefulness, coolness and relevance – ironically mostly on Twitter itself. In the context of science, for example, Twitter can make conferences more enjoyable and interactive, allows for self-promotion and is an excellent tool to stay updated about recent publications and developments (e.g., here). Although I am not very familiar with the marketing and journalism communities, I imagine Twitter is one of the favorite – if not THE favorite – social media platforms for similar reasons. Also the tech community and celebrities belong to the most avid Twitter users.

All these communities have one thing in common: They are highly educated professional elites that by the very nature of their job must communicate with as many interested people as possible. They (should) have something to tell and sell. They want to be heard. Or putting it the other way round, they are not the average person who lacks the ambition to reach beyond existing circles, such as family and friends. Consequently, the average Internet user (think about your mum, dad, uncle or friends from primary school) does not see the point in Twitter. S/he doesn’t get its lingo and conventions, either (“retweet? mentions? 140 character limit? hashtag? lists? abbreviations? WTF??? why would anyone want to do that??”). Facebook, by contrast, caters to almost everyone because it offers more functionality and serves our basic interest for what’s happening in our wider circle of friends and acquaintances. It’s probably easier to understand for the novice user than Twitter as well. On Facebook, the people that “have nothing to say” can still observe what’s going on, they can chat with their friends, participate in events and express their preferences via likes in a relatively closed environment (at least in their perception, whereas Twitter is mostly used in the public mode and thus accessible by everyone).

I think these basic differences in the perception can partly explain why Twitter struggles to increase their user base ( – despite mainstream media “promoting” Twitter to lay audiences, for example by showing tweets after sport events on TV or compiling Storifys.

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Connected Life 2015 – A Storify Conference Review

Here’s the link to my first Storify:
This is a summary of a very good conference I attended today. Enjoy the read – and the nice pictures!

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Towards a Computer Science Publication Model in the Social Sciences

In the next series of posts I argue how the publication system of my research area – Internet research with a background in media and communication as well as management – could profit from becoming more like the publication system in computer science, in a first step, and then physics, in a second step. However, as the social sciences of the Internet (which I consider myself being part of) are a very broad and interdisciplinary research area, I need to specify that the following explications only apply to the domains that I know: sociology of the Internet, political science of the Internet, (social) psychology of the Internet, and – partly –philosophy of the Internet as well as information systems. Thus, I refer to the major social science Internet outlets, such as Journal of Computer-Mediated Communication, New Media & Society, Information, Communication & Society, Computers in Human Behavior, Social Science Computer Review, Journal of Broadcasting & Electronic Media, Journal of Information Technology & Politics etc. I also include the open access journals, such as First Monday and International Journal of Communication, although in some ways they are different/better. But how is the publication system in social science Internet research (and probably also in other social science fields) flawed?

  • It takes too much time from submission to publication
  • The review system isn’t efficient and often quite arbitrary
  • The system places too much weight on the publication brand (journal reputation, impact factor, rankings, h-index etc.) and not enough weight on the content, i.e., the research results and the novelty and ingenuity of findings

Ad Point 1): Research productivity and progress is severely inhibited by the long time it takes from submission to publication. Often, research in this domain substantially lags current social developments, so that the data are frequently several years old when a publication goes online. This is very problematic, since the Internet is a rapidly evolving field of study, where it is especially important to stay up-to-date (so as to inform current debates in policy and media, for example). Normally, it takes at least several months and in some cases – with all revisions – even years from submission to publication. Of course, good research takes time, but this is time that was already invested at the time of submission and shouldn’t be unnecessarily extended once the results are written up.

The long process from submission to publication includes several problematic sub-points: stupid formal requirements, retaining journal issues in the digital age, no early view and long time from acceptance to publication. Many journals require their authors to fulfill completely stupid and arbitrary formal requirements, such as exotic citation formats, the use of endnotes (instead of footnotes or no such things at all) and very special table formatting. Every time an author has to resubmit a rejected article to another journal, it takes forever to update the formalities. It would be a great first step to reach agreements among the publishers and journals to have one – and only one – set of formal requirements. Better so it would be to do away with such requirements completely and let the authors write as they want – publishing the unformatted raw text (much like a post-print but maybe with subsequent page numeration) as the final version. This leads to the next issue: the issue issue. Journal issues slow down the publication process immensely and should be disposed of entirely. Once an article is published online (nowadays referred to as “early view” or “early cite”) and has a DOI, this should be the final, citable version. Journals without early view should introduce it as soon as possible. What’s the point in holding articles back for several months, when they could be published right away? Finally, and this is somehow similar to the last sub-point,  journals should do their best to make the time spans between acceptance, copyright agreements, sending out the formatted version to the authors, implementation of the proofs and (early view) publication as small as possible. The whole process from acceptance to publication should take a couple of weeks, but not entire months.

In the computer science publication model the submission-publication cycle is shorter, because the conferences provide clear deadlines in terms of reviewing and presenting. The standardized format and the clear communication of relevant information, such as acceptance rates, the reviewing process, the conference fees, the conference structure and the nature of the proceedings as well as their accessibility allows for more predictability for the authors. Of course, the computer science publication system is far from being homogenous and perfect – and there are many criticisms within the field ( – but I think it would be a first step of advancement for the social sciences to go into that direction.

More on the second and third points soon.  

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The Ghettoization of Facebook

(Disclaimer: I first wanted to name this post “Applying dynamics of urban sociology to the Internet”… I think “The Ghettoization of Facebook” is much sexier, though)

Can we analyze the digital sphere with the same concepts that have proved helpful in describing urban developments in the “real world”? Yes, we can! Today, I want to apply two such concepts to the Internet: gentrification and ghettoization.

Gentrification, according to Wikipedia, refers to “shifts in an urban community lifestyle and an increasing share of wealthier residents and/or businesses and increasing property values.” ( Ghettoization describes an opposite process, namely decreases in value of certain areas and a decay and loss of quality of life for the inhabitants. Ghettos are characterized by – mostly racial or socio-economic – segregation and poverty. (

In my opinion, both concepts are fruitful to analyze processes on the Internet. Gentrification takes place when thriving, creative platforms are taken over by wealthy investors and powerful companies – mostly with monetary interests. Examples are the acquisition of Mendeley by Elsevier or the incorporation of Youtube into Google. Both Mendeley and Youtube were darlings of the artsy early adopters, of the creative communities on the Internet: Youtube of independent singers, movie directors and artists, and Mendeley of open access advocates and progressive scientists. Neither Youtube nor Mendeley have substantially changed their business model after Google’s and Elsevier’s takeover but small adaptions indicate a gradual incorporation of new principles. Youtube, for example, has been increasingly tied to Google+, making it more streamlined and corporate than it used to be. When these platforms become gentrified, the early users tend to move on to other services, where they find fertile grounds for their creativity. Former Mendeley users move to Zotero. Vine offers new opportunities for the fed-up Youtubers. The same is true for Facebook. The recent buzz about Ello proves just how eagerly the early community/the social media avant-garde is waiting for a valid alternative.

It is true, Facebook shows increasing signs of ghettoization. Annoying ads, poor content filtering, and an ever-increasing overload of functionalities make the site a wasteland for many. At the same time, the fact that one’s friends are still there and the previous investments (curating photo albums, promoting events, joining groups and liking pages to stay informed etc.) complicate the goodbye. What I observe in this scenario: The “I-don’t-give-a-fuck” users post crappy “fun” content more frequently than ever, while the considerate and moderate posters of the past shy away from any activity and become mere lurkers (or almost-non-users) – or they don’t post in “public” (i.e., on their newsfeed) but in groups or in private conversations via the messenger… Or they gradually move to other platforms, as is the case for the gentrification processes described above. In this light, Facebook becomes ghettoized and the – relatively – new findings that social and entertainment content production is negatively connected to income (Blank 2013) and education (Hoffmann, Lutz & Meckel 2014) make sense.

Interestingly, the same process seems to have taken place for Myspace some years ago. I guess these processes occur because social network sites – and also content platforms like Youtube and Mendely – are designed to bear some sort of sociality (be it explicit, as in the case of Facebook or more implicit, as in the case of Mendeley, where users read each other’s article and build a scholarly community). In essence, they are social platforms. Both gentrification and ghettoization are disconcerting trends because they entail homogeneity and a lack of diversity (in the case of gentrification, the rich crowd out the creative and working class; in the case of ghettoization the poor and under-privileged are crowded out and – implicitly or explicitly – forced to stay among themselves).

At the same time, we still know too little about the social processes of distinction on the Internet. As always, more research is needed 🙂


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#ICA14: The Digital Divide and Big Data

At this year’s ICA conference in Seattle (pretty nice city, btw!) I laid a strong focus on the digital divide. Not only did I attend the pre-conference on 20 years of digital divide research ( and present a paper there; I also gave a presentation in the very last session of the conference on content creation and the participation divide in Germany ( The vivid research agenda on the digital divide and several presentations in this area were among my personal highlights of the 2014 ICA conference.

Two other highlights included:

  • 2 panels on big data and computational social science: „Really Useful Analytics and the Good Life“ and „Emerging Research Agendas at the Intersection of Communication and Computational Social Science“
  • A presentation by Alice Marwick on online self-branding within the panel “Venture Labor”
Alice Marwick's presentation on self-branding was one of my personal highlights of #ICA14.

Alice Marwick’s presentation on self-branding was one of my personal highlights of #ICA14.

During the conference, one aspect showed up irregularly and it’s worth treating it in more depth, since it hasn’t found the attention it merits. It’s the question of representation and making yourself heard and visible on the Internet. Here, interesting connections emerge between the digital divide and the other highlights mentioned, namely the developments in big data and computational social science and online self-branding.

How so? When we study the digital divide, it’s not only about Internet access, online skills, ICT use, participation/content creation and all the gratifications that emerge from there. It’s also about who is visible on the web, which impressions and traces individuals leave online, and how these can be manipulated and monitored. Such aspects merit more attention, as their importance will only increase in the immediate future. In short, “what I do online” should be complemented by “what’s out there about me online” – and what others make of me online by (not) writing about me, by (not) liking my content, (not) endorsing me or (not) knowing me, i.e., being friends with me or following me. In this vein and in the tradition of digital divide research, researchers should investigate the ones who are NOT represented and canNOT make themselves heard – be it directly via participation or indirectly via less obvious paths, such as business analytics, predictive analysis or big data. There is a danger that companies establishing their offers and business models by means of big data analyses will only consider individuals who are present in their datasets. Data-rich,  i.e., prominent, users on the web derive a bigger benefit from these new offers and are served more accurately and individually than users who are not (or only marginally) represented online. Thus, they are twice advantaged: First, because they are more prominent in the first place, better findable and less obscure. Second, because new services are increasingly tailored to their specific needs and they profit more from that.

Research on the digital divide should increasingly turn to the question who’s findable and present on the Internet, who’s able to build him/herself a public and who is not. A current Oxford Internet Institute study goes in that direction. It shows, with a large-scale analysis of Wikipedia data, how unevenly the world is encyclopaedicly cartographed ( „There is simply not a lot of content about much of the world“. Furthermore, the study shows that the underrepresented regions are often described “colonializedly”, i.e., not in their own language but by better represented countries and language regions. Jen Schradie, who also presented at the ICA conference, wrote an inspiring article on that issue. She observes that big data excludes primarily the underprivileged and is therefore not big and inclusive enough (

The concept of self-branding plays an important part, too. Alice Marwick stressed the de-emancipatory potential of the social web during the ICA. The ones who skillfully market themselves online and promote themselves as a brand, with constant – often superficial – status updates, can shape their self-image in a proactive way and make themselves heard. By contrast, shy and less self-confident (and thus less self-branding) users will perish. Social media providers, via their interfaces, smartly program and foster such forms of self-promotion. Thus, they contribute to the widening of the big data divide. Online, the thought of branding yourself as a product, as a perfectly trimmed commodity, becomes increasingly pervasive.

Snapshot of Alice Marwick's #ICA14 presentation with an example of a self-branding advisor.

Snapshot of Alice Marwick’s #ICA14 presentation with an example of a self-branding advisor.

What can we do? How can we counteract these worrying tendencies? There were a couple of answers to these questions in the other highlights mentioned above. The panel „Really Useful Analytics and the Good Life“ showed ideas and initatives how big data can be brought back to the ordinary individuals and to the communities. Among others, „analytics should be accessible and available to all publics to use”, „analytics should be open to public supervision“ and „analytics should be subject to democratic control in the public“. Nick Couldry from LSE presented a promising project in these regards, where scientists, developers and common people collaborate: Storycircle  ( attempts to create awareness of the most recent developments in the area of social media and big data by means of workshops and a participatory action research framework.


Tweet during #ICA14

Tweet during #ICA14


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Self-disclosure and the “art” of not losing friends on SNS

Reading a little bit of self-disclosure and privacy literature recently, I asked myself (and you, readers!): What’s the best way for not losing friends on Facebook? Thinking very strategically, I should probably thoroughly analyze my social network (using social network analysis) and derive some sensible approach to serve the various needs of my ego-network with my status updates. I could come up with a differentiation of my Facebook friends, for example by using a clustering algorithm (Girvan-Newman or something similar). The software would then detect social circles in my social network. In my case, these could be: family, friends from elementary school, friends from high school, friends from my studies, friends from my stay abroad in Spain, friends from my PhD, friends from holidays, and some random friends from different points in time – some of them probably isolates.


Once these circles are identified, I could think of the risk profiles and answer the question: Members of which circle are most likely to unfriend me? I should target my attention to these groups. In my case, more distant contacts, with whom I have only shared little time, would be a risk group. So, let’s say friends from my stay abroad in Spain and friends from holidays are more likely to unfriend me than friends from high school and friends from my PhD. In a next step, I would consult the Facebook unfriending literature (e.g., the work by Sibona and colleagues: Here, I would find useful hints on the determinants of unfriending. Sibona and Walczak identify the following reasons why people unfriend: frequent and unimportant posts (“spam”), polarizing posts (“flaming”), inappropriate posts (“trolling”), and everyday life posts (“bores”). In addition, disliked behavior and changes in the relationship in “real life” also increase the likelihood of being unfriended. As a (more or less) sensible human being, it’s obvious that I don’t spam, flame and troll on Facebook. Hence, the first three recipes against unfriending are easy to implement. However, the fourth point (“boring your audience”) is a little bit more tricky because of context collapse. What my PhD friends might find interesting is very boring to my high school and holiday friends. Pictures that friends from my stay abroad in Spain understand and find awesome might be annoying for some other random friends (who might be critical of Spain’s colonial past).

In a highly segregated social network – with many different social circles – on Facebook, the best solution against losing friends is probably to disclose little and only consensual success stories, which are of interest for everyone, such as the passing of exams, a new job, a nice beach holiday or a link to a non-controversial and positive news site (the Buzzfeed effect). That way, nobody is harmed or insulted. Still, the pitfalls of disclosing little become immediately apparent. Some people regularly scan their Facebook friend list and delete people who they haven’t had contact with for a certain time or from whom they haven’t seen an interesting post in a while. You have to make yourself visible to these “users at risk”. The key is monitoring: Know your social network and know the different circles as well as individuals. Write birthday messages to the “at risk people”, comment their status updates in a friendly and complimenting way, maybe also have a short chat if they want to, show genuine interest blablabla…

Of course, such a social desirability-driven approach goes hand in hand with self-censorship and the lack of authenticity. In the end, users need to decide what they want: a more authentic but maybe less streamlined and more “scandalising” online-personality with less friends OR a catch-it-all, polished and uber-shiny online-profile with few unfriends. One might ask: Is it worth all the effort? Is this very strategic approach even necessary? No, in my opinion not 😉 At least not for me.. and probably not for most people. (But some might be very offended and hurt by unfriending. For them, such guidelines might be useful. I myself don’t unfriend people on Facebook… EVER. I think it’s rude and unfriendly)

In terms of research, the relationship between one’s social network – i.e., its diversity, homophily, clustering, centralization, size etc. -, the frequencey and type(s) of self-disclosure and the subsequent formation (friending) as well as dissolution (unfriending) of ties is so far understudied. We need more data and evidence on this:





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