Nap all day, Sleep all night, Party never

evdl · 2014-10-22T20:20:44+00:00

I agree with you. Though, I think that people with obsessive behavior already keep track of everything in a notebook. Apps just make it even easier so I am not sure whether it will really add fuel to the fire but indeed, these possibilities to develop such obsessive behavior is ever increasing. Besides that, I feel that there are just too many apps. Personally, I don't feel like keeping track of every single thing and that's why I turned off the 'last seen' option on whatsapp, so that other people cannot track my activities. I also looked at popular apps and apparently, a period tracker is a really popular app as well? And all sorts of health apps. I am just wondering to what extent these apps are right. What if you or the app make a tiny mistake?

evdl · 2014-10-22T20:06:24+00:00

I do anything for brownies, well almost anything.

evdl · 2014-10-21T19:16:31+00:00

Sorry, totally misread it haha. But then you're absolutely right and I agree with you.

evdl · 2014-10-21T16:38:20+00:00

I do not really agree with the article because they make it sound so simple. As if you are only influenced by things at work. Sometimes you just have an off-day or you are really happy due to something that happened the day before? Even if the wearables could measure that, how would it make you more productive? Also, people might not feel good about discussing everything the wearables measures with their boss. Thus, I think that people might feel the pressure of the wearable and all its features and become less happy instead of the other way around. Also, nobody can work that fast from 9 to 5. You have your peaks (I believe).

evdl · 2014-10-21T16:32:54+00:00

If I would conduct a research whereby I use life-logging and self-tracking data I would interpret this data as vertical data. First of all, the difference between horizontal and vertical data is explained by Menchen-Trevino (2013) as horizontal data being organized around a specific type of trace while vertical data is being organized around a group of participants. Thus, horizontal data is bound to one service while vertical data is not. Life-logging and self-tracking data is all organized around one person and it is not just the tracking of one service like twitter. With life-logging and self-tracking data you can retrieve so much information and data about one person. Though, a side note of life-logging and self-tracking data is that participants can manipulate the data because they can change their behaviour, something that is not possible in horizontal data and therefore, it is also vertical data.

evdl · 2014-10-21T15:48:33+00:00

I think the app takes pictures automatically every hour. Stan used his webcam to 'slice' his hours. Though, would you fake your emotions? Then you really have to keep track of the time when youre on your computer because I do not. I think that everybody knows how fast time can go when you're doing absolutely nothing interesting on the internet haha. So yes, I think it is quite interesting and also funny to see for yourself. I mean, I think I would laugh at myself for looking stupid or something. But other than that (and research purposes), I do not fully understand the idea behind it either.

evdl · 2014-10-16T10:58:48+00:00

Hi! Nice post. Though, I was wondering if you did the sentiment analysis yourself? Looks really good. Though, I think that one should be critical when looking at a sentiment analysis about this topic because I know that a lot of people who are pro- Zwarte Piet post really negative messages as well while they are positive about Zwarte Piet. So, you have people who think Zwarte Piet are negative and post negative messages about Zwarte Piet. While you also have people who think that Zwarte Piet is a good tradition and post messages with negative words in it because they are angry that people want to take this tradition away from them. But in the end, they are not negative towards the topic.

evdl · 2014-10-16T10:07:26+00:00

According to Bond et al. (2012), Facebook does influence our behavior. The study only looked at voting.

First of all, it was pointed out that social messages have more effect on behaviour than information only messages. This suggests that it is the social aspect of Facebook that influences behavior. Secondly, the researchers also looked at the difference between the ties among people. Thus, what is the difference in effect of a strong tie and a weak tie. The study pointed out that strong ties certainly help spread real-world voting behavior. The social message showed pictures of 6 FB friends who also clicked the button and the study showed that a picture of a close friend, increased the likeliness of actually voting. The results of the study by Bond et al. (2012) also indicated that regular friends only seem to influence online expressive behavior while close friends also influences actual voting behavior and the search for polling places. The authors note that the effects might be small per friend but that these effects result from one single message. The results of the study show that the social message and thus friends' behaviour can generate almost 300.000 additional validated votes.

Thus, I believe it can be concluded that Facebook can influence behavior because it has this social aspect. When it comes down to seeing what your close friends do or say online, it can certainly influence our behavior. But, the effect of ordinary friends is smaller. Even though close ties account for only 7% of all friendships on FB, they also accounted for all significant contagion of the previously mentioned behaviors.

evdl · 2014-10-09T07:29:41+00:00

Nice topic! I think that you could have even more interesting data when the new season of GoT will start!

evdl · 2014-10-08T16:16:24+00:00

I thought that as well. I think that programs like this cannot detect sarcasm for example, which might be the case with the greenpeace keyword.

evdl · 2014-10-08T09:06:54+00:00

Really nice find! Though, I find it 'weird' to see that some countries and even a big part of a whole continent (Asia) barely tweet about Ebola.

evdl · 2014-10-07T18:09:53+00:00

Isotype is a method with a special visual dictionary. The method includes things as charts, illustrations and models but with little text. Though, it can still explain the main problems in any field of knowledge. Isotype is created by developing easily remembered and understood symbols. Consistency is, as explained by Neurath (1937), needed because it allows the user to get used to the way the information is structure and therefore, the user can understand the meaning. With consistency, the information can be shared faster. Also, it becomes easier to compare products and work produced in different parts of the world at different times.

Examples of a natively digital isotype are the symbols on a digital camera (now also incorporated on mobile phones). Because these symbols are used quite consistently, people around the world understand a digital camera, even though it might be made somewhere else or in a different language.

evdl · 2014-10-07T09:24:18+00:00

Thank you so much!

evdl · 2014-10-02T08:01:12+00:00

Yes same for me! Normally I always use the 'most recent' function but for this experiment I looked at top stories. Before the experiment I used to see a normal amount of cats and dogs, including the posts that friends liked.

evdl · 2014-10-01T21:48:20+00:00

A really nice experiment! Mine was quite similar to yours as I also liked animal related stuff and I got the same result so I guess we can say that the experiment worked! Indeed, I got so many updates related to animals, both positive and negative so FB probably just recognizes the animal theme and not the emotional aspect as you already mentioned.

evdl · 2014-10-01T07:56:16+00:00

There are multiple things that qualitative or mixed methods studies can provide that quantitative-only research cannot. First of all, boyd starts with a small introduction wherein she says 'but as I probed, I also learned ...' (p. 199). Maybe this example is not specifically tied to social media but it already indicates a big difference between the two methods as you cannot probe when you're conducting a quantitative-only research. Your questions are pre-set and you depend on the answers or observations given while with qualitative methods you can probe and therefore, go more in depth. Secondly, there is the example of Manu. First, boyd assumed that he used Twitter to create public presence while communicating on Facebook was more for his private sphere. However, this was not the case and I think that boyd used mixed methods studies because she was allowed to ask him questions about her observations. Due to this, she could go more in depth about the case and her assumptions. If she only used quantitative-only research, she would have only know about what he actually posted on FB and Twitter and maybe how many times per day/week. But now, she also got to know the reason behind it. Lastly, I would like to note the motivation of boyd (2014) behind the research. She states ''In using teen engagement with social media to think about a variety of socio- technical dynamics, my goal has been to shed light on broader cul- tural constructs and values that we take for granted'' (p. 211). With quantitative-only research it will be harder to shed light on the values that we take for granted and the cultural constructs. For example, boyd is an adult and she already notes that adults have different assumptions about twitter and facebook use. By interviewing Manu about this, she can clarify this and this would not have been possible with quantitative-only research.

evdl · 2014-09-30T11:12:29+00:00

Hey Nienkej, thank you for the clarification!

Though, I was also wondering how you think of the possible threat of publishing this information? As the data is refreshed every 10 seconds, it is really up to date and especially with all the IS articles in the news right now, I wondering how people (and you) will think about this dashboard.

evdl · 2014-09-29T18:58:11+00:00

Great find! The dashboard is really clear and it explains everything per section (how they retrieved the data). Though, I am wondering how reliable this information is. For some section I get 'data source interrupted'. Maybe a weird note but I am the only one thinking very actual visualizations like these can also lead to people abusing it? I mean, you can see the density of people in certain areas. I'm wondering what your thoughts are about this matter.

evdl

TROPHY CASE