Monopolization of community-based information networks by cartels of a few “super editors” among several risks that could lead to a diminished Wikipedia
Wikipedia’s quality benefits from high levels of free participation, but volunteer information databases like Wikipedia can be negatively effected by tendencies toward information monopolization, and, according to a recent study, this negative effect is more prevalent in more frequently edited articles — articles that could be considered to be more important.
In the study, researchers at the Korea Advanced Institute of Science and Technology and the Korea Institute for Advanced Study looked at how editors interact with each other as well as how they interact with articles, and integrated previously-ignored factors such as the consideration of real time — not just the number of edits used in previous studies to mark time.
Among the team’s findings: infrequently-referred articles grow faster than frequently-referred ones. Not only that, but articles that attracted a high motivation to edit actually reduced the number of participants. Yun and his colleagues inferred that this type of Wikipedia article participation decay results in inequality among community editors. The trend will become more severe as time goes on, they suspected:
“For the previous decade, many of these open-editing access movements have significantly affected the entire
society,” Jinhyuk Yun, a Ph.D. candidate at the Complex Systems and Statistical Physics Lab at the Korea Advanced Institute of Science and Technology in Daejeon, South Korea, told us.
“Wikipedia, Creative Commons Licenses, GNU, etc. To sustain such movements, they must maintain their motivations for participants, which might be taken away by monopolization.”
Yun explained how communal information databases like Wikipedia slow down.
“There are various reasons to participate in such ‘open-editing’ movements. Some are collective reasons shared in a society, and others are somewhat personal. Because the motivation is diverse, slowing down is also due to various causes. First, there can be a loss of necessity to contribute due to changes in society — or technology. Some GNU software based on old platforms no longer continue because the number of users of such software is getting smaller. In addition, there can be new barriers caused by governmental regulations — not about such communal databases, but considering the case of UBER. One particular candidate we discussed in the paper is the monopolization by few ‘super-editors.'”
Yun also commented on how we can consider the health of such community databases?
“It is very hard to quantify the ‘health’ of such database because of the ambiguity in the definition of health. In my point of view, the databases should meet the standard of accuracy and instantaneity. In other words, it should keep the trend, but it should not lose its accuracy in the contents. Although these databases are mainly based on the contribution of anonymous sources, it should also have reliable references to cross-check.”
However, data monopolization is not a black and white issue, Yun noted.
“To be honest, monopolization sometimes does good in particular occasions,” Yun told us, “yet it has many risks in most cases. Consider political issues in authoritarian governments, where media controlled by the government sometimes manipulates people’s opinions by a simple nudge or filtering. Such manipulation can also happen in Wikipedia — for example, by cartels of super-editors.”
Yun offered some possible remedies for content monopolization on Wikipedia:
“Based on our observations, Wikipedia could consider a reward program to recruit new editors. Simple achievement reward programs — like those in video games — at an early stage might be helpful, yet it should be done under strict supervision to avoid vandals. For instance, giving merit to editors who supply new reliable references might help to keep the quality of articles.”
The report, “Intellectual interchanges in the history of massive online open-editing encyclopedia, Wikipedia” was completed by J. Yun, S. H. Lee, and H. Jeong.
By Andy Stern
When political parties reverse their policy stance, their supporters immediately switch their opinions too
At least a significant portion of their supporters, according to U of Aarhus researchers.
When two competing political parties in Denmark reversed their policy stance on an issue — suddenly they both supported reducing unemployment benefits — their voters immediately moved their opinions by around 15% into line with their party.
The same thing happened when one of these parties shifted from opposing to supporting ending Denmark’s early retirement.
The researchers were studying how public opinion is formed. Their recent paper sheds light on how much influence political parties have over their supporters, according to the researchers, who surveyed their panel of subjects in five successive waves between 2010 and 2011. They studied the same group of party supporters before, during and after a policy reversal.
“We can see that [the] welfare programs were actually quite popular … and many of the voters of the center-right party were in favor of these welfare programs,” commented one of the researchers, Rune Slothuus. “Nevertheless, we can see that they reversed their opinion from supporting these welfare programs to opposing these welfare programs.”
“I was surprised to see the parties appeared this powerful in shaping opinions,” Slothuus said. “Our findings suggest that partisan leaders can indeed lead citizens’ opinions in the real world, even in situations where the stakes are real and the economic consequences tangible.”
The researchers pondered Western democracy in light of their findings: “If citizens just blindly follow their party without thinking much about it, that should lead to some concern about the mechanisms in our democracy. Because how can partisan elites represent citizens’ views if the views of citizens are shaped by the very same elites who are supposed to represent them?”
Source: How Political Parties Shape Public Opinion in the Real World. Rune Slothuus and Martin Bisgaard. First published: 04 November 2020 https://doi.org/10.1111/ajps.12550
The brain listens for things it is trying to predict
The brain interprets sounds as they contrast with its expectations; it recognizes patterns of sounds faster when they’re in line with what it is predicting it will hear, but it only encodes sounds when they contrast with expectations, according to Technische U researchers.
The researchers showed this by monitoring the two principal nuclei of the subcortical pathway responsible for auditory processing: the inferior colliculus and the medial geniculate body, as their subjects listened to patterns of sounds which the researches modified so that sometimes they would hear an expected sound pattern, and other times something unexpected.
Source: Alejandro Tabas, Glad Mihai, Stefan Kiebel, Robert Trampel, Katharina von Kriegstein. Abstract rules drive adaptation in the subcortical sensory pathway. eLife, 2020; 9 DOI: 10.7554/eLife.64501
We have a particular way of understanding a room
When several research subjects were instructed to explore an empty room, and when they were instead seated in a chair and watched someone else explore the room, their brain waves followed a certain pattern, as recorded by a backpack hooked up to record their brain waves, eye movements, and paths. It didn’t matter if they were walking or watching someone else, according to UC researchers led by Dr Matthias Stangl.
The researchers also tested what happened when subjects searched for a hidden spot, or watched someone else do so, and found that brain waves flowed more strongly when they had a goal and hunted for something.
Source: Matthias Stangl, Uros Topalovic, Cory S. Inman, Sonja Hiller, Diane Villaroman, Zahra M. Aghajan, Leonardo Christov-Moore, Nicholas R. Hasulak, Vikram R. Rao, Casey H. Halpern, Dawn Eliashiv, Itzhak Fried, Nanthia Suthana. Boundary-anchored neural mechanisms of location-encoding for self and others. Nature, 2020; DOI: 10.1038/s41586-020-03073-y
Extroverts and introverts use different vocabularies
Extroverts use ‘positive emotion’ and ‘social process’ words more often than introverts, according to new research conducted at Nanyang Technological U.
‘Love,’ ‘happy,’ and ‘blessed’ indicate pleasant emotions, and ‘beautiful’ and ‘nice’ indicate positivity or optimism, and are among the words found to be used more often by extroverts. So too are ‘meet,’ ‘share,’ and ‘talk,’ which are about socializing. Extroverts use personal pronouns — except ‘I’ — more too, another indication of sociability.
The correlation, however, was small, and the researchers think that stronger linguistic indicators need to be found to achieve their general goal, which is improving machine learning approaches to targeting consumer marketing.
Source: Jiayu Chen, Lin Qiu, Moon-Ho Ringo Ho. A meta-analysis of linguistic markers of extraversion: Positive emotion and social process words. Journal of Research in Personality, 2020; 89: 104035 DOI: 10.1016/j.jrp.2020.104035
WhatsApp is changing today - Users must give the app permission to send their private data to Facebook or lose account
WhatsApp was bought by Facebook in 2014, but has thrived while promoting itself as a privacy-respecting messaging app that now has 1.5b monthly active users. This week, though, WhatApp sent out an update to users’ phones that they must ‘consent’ to a new policy or lose access.
Whatsapp will now share more of your data, including your IP address (your location) and phone number, your account registration information, your transaction data, and service-related data, interactions on WhatsApp, and other data collected based on your consent, with Facebook’s other companies. Facebook has been working towards more closely integrating Facebook, WhatsApp, Instagram and Messenger.
Users who do not agree to ‘consent’ to the new policy will see their WhatsApp account become inaccessible until they do ‘consent.’ These accounts will remain dormant for 120 days after which they will be ‘deleted.’
The biggest change to the user policy, which many people ignored and clicked ‘agree’ to, thinking it was just another unimportant app update message, now reads,
‘We collect information about your activity on our Services, like service-related, diagnostic, and performance information. This includes information about your activity (including how you use our Services, your Services settings, how you interact with others using our Services (including when you interact with a business), and the time, frequency, and duration of your activities and interactions), log files, and diagnostic, crash, website, and performance logs and reports. This also includes information about when you registered to use our Services; the features you use like our messaging, calling, Status, groups (including group name, group picture, group description), payments or business features; profile photo, “about” information; whether you are online, when you last used our Services (your “last seen”); and when you last updated your “about” information.’
Notably, Elon Musk tweeted on the news, saying that WhatsApp users should switch to Signal, one of several popular privacy-focused messaging apps similar to WhatsApp.
The data sharing policy change doesn’t affect people in Europe due to GDPR data protection regulations.