URLs of wisdom (24th May)

URLs of wisdom is a weekly round-up of interesting links about topics at the intersection of people, science and technology. This post covers content since 10th May.

Behaviour

  • You won’t finish this article – When people land on a story, they very rarely make it all the way down the page. A lot of people don’t even make it halfway. Even more dispiriting is the relationship between scrolling and sharing. Schwartz’s data suggest that lots of people are tweeting out links to articles they haven’t fully read. If you see someone recommending a story online, you shouldn’t assume that he has read the thing he’s sharing.”
  • Why we favourite tweets  “the “findings highlight that the favoriting feature is currently being over-utilized for a range of motivations, whilst under-supporting many of them….what the diverse range of motivations behind favoriting may show is that despite Twitter’s recent attempts to create an increasingly standardized and top-down user experience, it’s still a platform with a massively diverse user base that uses Twitter for many different reasons. And that if Twitter wants to remain an essential part of the conversation, it will take its cues from the way users want to use their technology, and not the other way around.”

Virality/Popularity

  • Who will RT this?  Development of a machine learning algorithm that picks users who are most likely to retweet on a certain topic.
  • Why that video went viral “If you want to melt the Internet, best to traffic in emotion, researchers have found. The emotional response can be happy or sad, but the more intense it is, the more likely the story is to be passed along.”
  • The ideal length of everything online 

People stuff

  • When Mothers TextI also have come to realize how cellphones can be used to express love. Often it’s not the big, all-consuming love. Instead, it’s love expressed in small ways.”
  • Designing for love – how can better design improve how technology allows us to connect?

Privacy 

Communities

Web/Social media developments

  • Twitter starts rolling out a mute button to silence people you’re following. Mute me argues that this a bad thing: “Now you can’t tell if someone actually wants to follow you, or is merely being courteous, political, or whatever else. The honesty of the follow is gone, and so therefore is some of the honesty that Twitter engenders in us.”
  • What is the outlook for Twitter? “we are increasingly tweeting to the events of our lives (from news events to concerts). Twitter thus fills an important gap in social media that goes beyond information exchange to making entertainment and other events more socially experienced.”
  • “Can there be such a thing as pure democracy online?” Interesting discussion of moderation and community management challenges on reddit.
  • Giants behaving badly  – Google, Facebook and Amazon show us the downside of monopolies and black box algorithms.

Just for fun

Running for President in the age of the Internet

 

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URLs of wisdom (10th May)

URLs of wisdom is a weekly round-up of interesting links about topics at the intersection of people, science and technology.

Network Effects

  • Complexity in social networks – Really good read about how 4 different features of the structure of networks affects the user experience. “One way to think about these technology platforms is to think of any complex network as having four fundamental components:
    • Nodes (the objects in the graph, e.g., people, things)
    • Data/content (the thing being shared between the nodes, e.g., tweet)
    • Edges with rules (e.g., bidirectional “friend”, single-directional “follow”)
    • Jumping functions, specifically ways to transmit the data/content from one subgroup of people to another on the same platform, usually based on rules surrounding how the edges are structured (e.g., retweeting / liking / favoriting).”
  • Combatting the rich get richer effect? A bot for tweets that get overlooked.

Behaviour

  • We need online alter egos now more than ever “The key to making pseudonymous participation productive is to inspire people to care about the impression they are making on others. In physical environments, the body anchors identity; online, one’s history of contributions and interactions functions as one’s “body”, but it can be difficult to see.”  

“Face to face, we develop relationships in separate contexts — and the things we talk about, the jokes we make, the secrets we reveal – vary tremendously . You may share, say, your feelings about the difficulties of caring for an aging, fading parent or a special needs child with others in the same situation; you may find things funny in the company of old friends that you would never admit to thinking humorous in front of your family. You present yourself differently to your neighbor, lawyer, teacher, children, grandmother — you use different words and talk about different things. This is not a lack of integrity, but a feature of being an adaptable person in multiple social contexts, understanding the varied mores of the different situations. Pseudonyms allow us to maintain such separate contexts online.”

“negative feedback leads to significant behavioral changes that are detrimental to the community. Not only do authors of negatively-evaluated content contribute more, but also their future posts are of lower quality, and are perceived by the community as such. Moreover, these authors are more likely to subsequently evaluate their fellow users negatively, percolating these effects through the community. In contrast, positive feedback does not carry similar effects, and neither encourages rewarded authors to write more, nor improves the quality of their posts. Interestingly, the authors that receive no feedback are most likely to leave a community.”

  • For the love of being liked – on attention-seeking on social media “While getting lots of likes or retweets feels great, the feeling of rejection from not getting them is often greater. People’s fear of being excluded is so intense…”

Privacy 

Web/Social media developments

Just for fun

What to call that event…?

 

URLs of wisdom (3rd May)

URLs of wisdom is a weekly round-up of interesting links about topics at the intersection of people, science and technology.

Network Effects

  • Rumour cascades on Facebook  “Online social networks provide a rich substrate for rumor propagation. Information received via friends tends to be trusted, and online social networks allow individuals to transmit information to many friends at once. By referencing known rumors from Snopes.com, a popular website documenting memes and urban legends, we track the propagation of thousands of rumors appearing on Facebook. From this sample we infer the rates at which rumors from different categories and of varying truth value are uploaded and reshared. We find that rumor cascades run deeper in the social network than reshare cascades in general.”
  • Ed Yong describes another recent online study of the Matthew effect (or “richer get richer” phenomenon). See also my post on an older study.

Behaviour

  • The great Facebook deep clean – Kevin Roose raises the interesting broader question of how you enable a user to keep her social network *socially* relevant over the long haul, when friendships fade and tastes change.
  • And related – Twitter testing a mute button to silence follows.
  • The networked selfie –Selfies tell a story. They reveal and they conceal, because that is what a story does. It makes some aspects of an event, a memory, a feeling more visible, and in so doing, it directs attention to certain things —and inadvertently away from others. But it is a story. It affirms who we are. We tell stories to make sense of things, our lives, our selves. To make meaning and in so doing, connect with others.”

Academia Online

Web/Social media developments

Lots of discussion about the future of Twitter after their first quarter earnings report disappointed some.

  • Is Twitter dying?  A lot of this argument comes down to what we feel. Communities can’t be fully measured by how many people are in them……From the beginning, there were a few useful precepts that those of us who have obsessed over the platform had to believe. First, you had to believe that someone else out there was paying attention, or better, that a significant portion—not just 1 or 2 percent—of your followers might see your tweet. Second, you had to believe that skilled and compelling tweeting would increase your follower count. Third, you had to believe there was a useful audience you couldn’t see, beyond your timeline—a group you might want to follow one day. Those fictions have proven foolish, one-by-one.”
  •  Twitter’s not dying, it’s on the cusp of becoming something much biggerTwitter is not a social network. Not primarily, anyway. It’s better described as a social media platform, with the emphasis on “media platform.” And media platforms should not be judged by the same metrics as social networks…Media platforms, by contrast, connect publishers with their public. Those connections tend not to be reciprocal.”
  • Twitter is no Facebook – and that’s fine.  “perhaps the modern world has room for more than one social service. LinkedIn and Twitter both do things — and do them well — that Facebook does not. Conversely, they do not do the things that Facebook does well. Ultimately what Facebook does best — help people keep in touch with far-flung friends and family — strikes very close to the universal heart of human existence, so it’s no surprise that it’s the biggest company.”

Other news…

  • Facebook’s anonymous login is evil genius  – “Developers are the mass at the bottom of the pyramid, and if they want access to the gold at the top — access to pretty much everyone who might ever buy their product — then Facebook is going to make them pay for it. It’s just good business sense. And if it can make them pay for it while simultaneously pleasing their users, calming their nerves on privacy while continuing to collect the same amount of information on them, so much the better.”  and an explainer of the changes here.
  • Five things – Obama’s big data experts warned him about – in the White House report released this week.
  • Beyond net neutrality  “The big challenge with this whole internet interconnection world is that everything is opaque.” 

Engagement and metrics 

“How do you even define “working”? Advertisers have their own favored audience metrics, but are they the best way to measure user engagement? The focus is often on time on site and repeat visits, according to Tom Negrete, The Sacramento Bee’s director of innovation and news operations….But he argues newsrooms and journalists have an obligation to go further, to measure comprehension: Can an individual understand what was just read in a news story?”

There were various suggestions on how to reimagine comments — from inline commenting to encouraging commenters to respond to a specific question posed about the article. A consensus among the participants was that increased interaction with newsroom staffers could help with the civility dilemma — but they also acknowledged that many newsrooms do not have the resources to devote staffers to mind the comments.”

Resources

  • New book (available free online) by Jono Bacon – Ubuntu Community Manager and author of The Art of Community. His latest offering, Dealing with Disrespect, offers advice on how to deal with online critics.

Just for fun

All that typing away on keyboards…what’s it all for?!

 

URLs of wisdom (end of March 2014)

URLs of wisdom is a weekly round-up of interesting links about topics at the intersection of people, science and technology.

Network analysis

Behaviour

  • Twitter’s root injustice – Why it’s so hard for new Twitter accounts to attract new followers and what Twitter could do to make things fairer.“…the real issue is the network effects that come from being first. It’s a classic platform problem. Every time you’re followed it gets easier for others to follow you because you have a bigger audience more likely to spread your message to more people.”
    (see also my earlier blog post on “rich get richer” effects online)
  • The dangers of data-driven list making –  “…we sometimes mistake optimization for inspiration. Data is for optimization; humans are for inspiration. Expecting the former to give you the latter is a bad thing.”
  • The importance of recognising cultural diversity in understanding online behaviour –  Zara Rahman argues for the importance of understanding cultural background before making grand statements about the internet: “This is, I feel, what has been missing in the work by many other internet commentators: a genuine understanding of the offline culture in the countries they’re talking about, and an appreciation for how the offline society and politics affects the way people use the internet.”
  • Creeping connectivity – work and life in a hyperconnected world – Krystal D’Costa takes a look at changes in the structure of a working day and how technology has facilitated that.
  • Oops – sorry for being so creepy – light article on the gaffes that we make with technology

Academia Online

  • Privacy in sensor-driven human data collection – a guide for practitioners. Paper considering how to deal with the ethical concerns of studying big data about human behaviour.  “Protecting the wellbeing of the participants of the studies in any domain is of utmost importance. The trust that exists between the participants and the researchers is even more difficult to establish and maintain when the amount and resolution of the collected data increase.”
  • Candle in the dark – On the importance of being visible online.
  • MOOCs of every shape and size – a comparison of different MOOC providers with an interesting infographic splitting out the two different types of MOOCs. (See also my write-up of my first MOOC experience)

Communities

Web/Social media developments

Resources

  • I started a Twitter list of network science tweeps. Suggestions welcome!
  • Interesting set of list of top astronomers, physicists and philosophers on Twitter by number of followers plus listing of top tweets. Note that many of these accounts don’t tweet that much on a daily basis…
  • The AAAS folks have been busy creating Storifys of sessions from the annual meeting that took place in Chicago in February. Overall summary of the meeting. Summary of the session on using social media for science communication and the one on engaging with public events.
  • I found this fantastic free online book, Network Science, which is being released online chapter by chapter.

Just for fun

Do you really need to read the manual…?

Instant replay: how a study of online communities helps to re-run scenarios in order to understand popularity

In the last post, we looked at how groups behave when binary decisions are involved. There, it’s assumed that each individual in the group has their own threshold that needs to be exceeded before they’ll take action. Granovetter’s riot model provided a useful place to start thinking about why the interactions amongst individuals in a group are important, but the simple threshold model doesn’t take into account more complex dynamics that are involved in social relationships or how these might affect decision making.

One noted social phenomenon  is cumulative advantage (also known as preferential attachment). Here, once a few people express their liking for something, it will become more popular still, and any differences between the popular choice and any less popular alternatives will be amplified.  Cumulative advantage tells us that it’s the number of people that like something that’s important to its success – not necessarily any intrinsic qualities of the object itself.  As Duncan J. Watts argues in his book Everything is Obvious, this goes against our common sense feeling that it must be that a popular item has some special, distinguishing features.

If we had the chance to repeat life multiple times, we could test which of the two ideas was actually true. If it’s the intrinsic features that are important, we’d expect that every time we replayed history, the same item would emerge on top. But if cumulative advantage is at work, then different items might emerge as favourites each time.

But of course, we only get to play history once. And this is where the internet becomes an incredibly useful tool for studying network effects – the large numbers of users and ability to create different online environments can allow hypothesis to be tested in multiple parallel situations, as if history were being allowed to play out several times. This is nicely demonstrated by Watts and his collaborators in a fascinating 2006 study of an online community of people interested in listening to music (no, not YouTube!).

Do you like what you hear? Image credit: Photo by Flickr user Mark JP http://www.flickr.com/photos/pyth0ns/6757854133/

Do you like what you hear?
Image credit: Photo by Flickr user Mark JP http://www.flickr.com/photos/pyth0ns/6757854133/

In the experiment, participants from a teen social network were recruited to a site called Music Lab, specifically created for the study. Each visitor was assigned to one of two types of condition – “independent” or “social influence”. In both cases they were asked to listen to and rate songs and given the opportunity to download them.  In the social influence condition participants could also see how many times others had downloaded the songs – the “social” aspect.

Over 14, 000 people took part in the experiment. The researchers divided them into 1 of 9 different “worlds”  – 8 of which had the social feedback about downloads displayed to members. All worlds featured the same 48 songs and started with download counts at zero. As songs were downloaded, this social data contributed only to the specific world where the song was accessed so that each world provided an independent repetition of the study. The additional group that wasn’t shown any social feedback provided a control for quality – given that participants couldn’t see what anyone else had downloaded, it was assumed that songs that became popular there might be the ones that were intrinsically better.

So what happened?

Where downloads were shown, the social input did influence what other users downloaded, and popular songs became more popular than anything in the independent, non-social conditions. What proved to catch on in one social world was also quite different to what was popular in another. So social influence increases not just inequality in decision making (“the rich get richer”), but also adds an element of unpredictability.

Interestingly, for those interested in online marketing, the whole experiment was also repeated to compare the layout of the songs on the website – displaying the songs as a ranked list in one scenario but as a random grid in another. The ranked list provides a clearer signal about the preferences of other users, and unsurprisingly, resulted in even more inequality and unpredictability about which songs would end up topping the ratings.

The results as a whole were even more dramatic because the experiment as a whole was likely to represent a toned down version of the social signals than might be observed in the real world, where marketing tactics and even discussion amongst users might be taking place. Finally, just in case you’re wondering if the experiment merely revealed some quirks about teenagers’ music tastes, the study was also repeated with adult participants with similar results.

So, after considering riots and music preferences we’re starting to get a feel for the importance of capturing the relationships between individuals if you want to understand group behaviour. Next, we’ll move onto thinking about the role of influencers in prompting changes in behaviour.

References/further reading

Everything is Obvious – once you know the answer – Duncan J. Watts – Chapter 3 – The Wisdom (and Madness) of Crowds

“Experimental Study of Inequality and Unpredictibility in an Artiifical Cultural Market” – Salganik, Dodds and Watts (2006). Science Vol 31. 854-856.

Preferential attachment (cumulative advantage) – this has been used to explain links to pages on the Internet and differences in citations of scholarly articles.