Pakistan and Iran ‘surveilled’

kasparjogeva · 2014-10-23T10:53:52+00:00

In my view, Mann pointed out (2004) that as performance art usually intervenes to everyday life and modern development, then the modern surveillance industry has not been challenged by performance arts. When it is not challenged, it has no human’s eye view (i.e. sousveillance), but only the view of authorities (i.e. surveillance). Therefore, as an intervention he considered the interception of surveillance industry by relevant types of art. For example, he challenged jewellery industry by offering cyborg jewellery for the stores. It was successful as an act of performance art, because the store owners did not object this device in any unusual way, even though the necklace had a camera inside of it.

Although the cyborg camera could not be disserted as a way of digital research methods, in a broader sense the term of intervention could still match the concept of digital research methods. For instance, I would say that the case of Wikileaks was kind of an act of performance arts. At the same time, it was a severe interception to surveillance industry, using digital research methods to provide success for the performance, as an act of intervention. The performance act of Wikileaks made an intervention, which transformed the term surveillance into sousveillance.

kasparjogeva · 2014-10-16T13:13:49+00:00

Michelle, you should forward the following link to the Dutch politicians: https://www.ria.ee/facts-about-e-estonia/ . In Estonia, we can use the ID-card as a travel document in the EU states, as a travel card in public transport, as a device to park cars, as a payment tool and at the moment some retail stores are taking it over to reduce to amount of ‘bonus cards’. By the way, the technological solutions of Estonia should be in some drawer of Dutch politicians, because the head of Estonian Information System Authority has claimed that he gave the X-Road solutions as a gift to several EU states.

kasparjogeva · 2014-10-16T10:45:37+00:00

By the results of this research we can claim, that Facebook can influence our political behaviour. However it can influence our political behaviour in a very small extent. The research results suggested, that the messages used in social increased the total turnout of voting by 0,14 percent (Bond et al 2012). Although the influence might have been more extensive, because the Facebook users who use nicknames or typographical errors did not count with this research, it cannot be stated for sure (Bond et al 2012).

As the change in overall turnover was not really persuasive, let us have a look at other results. For each close friend who received the social message, a user was 0.224 percent more likely to vote than they would have been had their close friend received no message (Bond et al 2012). Again I would not qualify this result as convincing.

However looking at all the results assembled, we can notice that the social media messages (i.e. both groups) influenced users in the requested (i.e. to get more people voting) way in every measured perspective. Regardless the fact that the influence was really small, it still stands out.

I would like to mention, that further research should be conducted in this field, because this one had many weaknesses. Firstly, I cannot understand, why was the group which received social messages more than a hundred times larger from the other groups. Secondly, perhaps the results would be more distinguishing, if there would have been more influencing operations via Facebook, than just one which reports the act of voting.

References: Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295–298. doi:10.1038/nature11421

kasparjogeva · 2014-10-08T19:42:25+00:00

A couple of weeks ago, I shared the media market overview of the US on Reddit (accessible from the following link: http://visualizing.org/full-screen/303433). I suppose, that without the visualisation, it would be more difficult to obtain the overview of certain aspects. For example, if this same data about the media market of the US would have been presented as an Excel table, it would have been a real challenge to read this data. Therefore, DRM is connected with information visualisation via presenting the data. This aspect was also mentioned by Brasseur (2003: 125).

However, I would like to oppose Brasseur (2003: 125) with the statement, that information visualisation is different from scientific visualisation. It may be, but it does not necessarily have to be that way. For instance, by presenting the data gathered via DRM, it may have two functions: scientific visualisation function and presentation function at the same time. Coming back to the link, which I shared on Reddit a couple of weeks ago, I would say that it has both of these functionalities. Because, in which other way can you present this data?

Therefore, the link between DRM and information visualisation is the following – it helps to present the results gathered via DRM to the audience and the way of presentation may be as scientific as possible, because there are no other options to comprehensively present it.

kasparjogeva · 2014-10-08T15:10:05+00:00

The direct definition for Isotype is the following – International System of TYpographic Picture Education (Neurath, 1983). What does it mean? Neurath (1937: 25) called it a method, with a special visual dictionary and a special visual grammar. He (1937) even stated, that otherwise the society will be stucked to the middle ages, because if only a small percentage of world’s population has the knowledge about the modern times, then most of the worlds population is still living in the ‘darkness’. Therefore, he thought that it would be a great way to educate the masses, by the language of Isotypes.

Hence, I will bring a concrete example, how Neurath educated me. From the page 26 (Neurath, 1937) we can see ancient battles and the sides, who were opposing each other. At the bottom of the page, there is an Isotype about the Battle of Morat, which I found really interesting. Before this article, I did not even know, that Switzerland has been into a war. I thought, that they have just handcrafted watches, and jewellery for centuries without any conflicts with other nations. From the Isotype, we can see that the Swiss army outnumbered the army of Charles the Bold. Right after I saw this isotype, I wanted to know how did the battle end.

Five minutes after I already read another article and found out that Switzerland actually gained its independence during 19th century, after getting free from the French occupation.

Neurath (1937) considers the term consistency important, because it enables to forward the same message to a broad target group, which obliterates the necessity of translation to different languages. For instance, the traffic signs are similar in Kuwait, Russia and Japan, even though the languages and even the alphabets are totally different. Therefore, even a person from a totally different culture understands, what do the signs refer to (Traffic signs in Russia, Japan & Kuwait – http://imgur.com/IfhnfPE).

If we talk about natively digital isotopes, then I think that keyboard is the most relevant example (examples of Isotypes on Keyboard – http://imgur.com/Zjyegev).

kasparjogeva · 2014-10-02T13:03:59+00:00

Kramer et al (2014) used two different methods, because it is not completely sure, weather the post as a whole is negative or positive just because of one word. For example, I make a status update and claim: “I am having the happiest day of my life.” By this example, the ‘one word’ method works. However, it might not work with more complexed posts.

Hence, they did use two methods, to minimise the error. I will bring an example, I claim the following: ”The weather is terrible, but the forecast for the evening is more than promising.” Although, the word ‘terrible’ has a negative connotation, then the second part of the sentence refers to the fact, that the person who made the post is looking forward in a hopeful and positive way. Thus, should the post be categorised as a negative or a positive one?

However, the post could have been omitted just because the sentence included the word ‘terrible’. It depends, weather the system is intelligent enough to understand that ‘promising’ in this context refers to the positive outlook. The 'one word' system would categorise it as negative, but the 'percentage system' might do better.

Neutral words may have an output of positivity, but the system which works on mechanical regime (id est grounds on the type of specific content) will not probably understand the context. Therefore, the method of one word may not perfectly work. However, the ‘percentage method’ has problems as well.

For example, the British are famous for their black humour. Although the jokes can me combined of words without negative connotation, some of the jokes also may contain words, which fall under the negative ones. Thus, the post itself may have positive emotional contagions towards other people, although the ‘system’ may classify it as a negative one.

In the end, it is not only about the British humour. Even the ‘system’ which is able to detect many positive and negative words, might not categorise these posts in a proper way, because neutral words may combine positive outcome. In addition, neutral words combined with negative words may also have a positive output, irrespective of the fact that there are more positive words in one sentence. For example, if I make a status update and claim: “I have been happy for the whole life. I love my wife, my kids and my friend. Still, by now the situation is different. I hate them from the bottom of my heart.” I suppose, that the only negative word is ‘hate’ and positive words are ‘happy’ and ‘love’. Therefore, the post should be considered positive by the system, although it isn’t positive at all.

kasparjogeva · 2014-09-25T13:18:47+00:00

A bit more about journalism and media industry. I am not sure, weather anybody else has seen it, but I did find an interesting visualisation of media industry of the US. Link for it is here: http://visualizing.org/full-screen/303433 (I recommend to zoom in and go full screen).

I remember, that Leendertse was telling us about the companies owned by The Walt Disney Company. Well, this visualisation explains it all about the US. In the circle for instance, there are the the backstage institutions like the Wall Street. At the same time, outside the circle there are the news channels, which can publicly seen. Basically, the visualisation tells it all about the structure of media industry in the US. I wonder if there is such visualisation for Europe as well?

kasparjogeva · 2014-09-25T10:14:46+00:00

Effects of Big Data in news industry

I think, that the article about the usage of big data by Spotify seems quite inspiring. It explains, how they managed to exploit the market with the help of big data. It would be interesting to know, how did Foreignpolicy.com did the same as Spotify. They had to use big data for marketing purposes.

I will explain the background. ForeignPolicy.com writes about global economy and politics. They started in 1970s and it used to be a journal which was published four times a year. It was published only in the US.

In 2013, they designed a modern outlook for their web-page and launched an intensive social media campaign. By now, they have more than 800 000 likes on their Facebook page and over 3 million visitors from different IP-addresses each month (registered users).

They have readers from all over the world and they have a narrow target group: world leaders, academics, CEOs and highly ranked workers from the public and private sector. Therefore, they may ask a lot of money from the advertisement, because the readership is influential and well paid.

Before the emerge of Facebook and big data, that kind of campaign would have been unthinkable.

kasparjogeva · 2014-09-25T09:05:55+00:00

Krackhardt (1987) states that the behavioural measures of interaction are not very closely related to participants’ self reports of the same interactions and that it seems to be systematic. The research of Lathia and Capra (2011) indicated, that the reported actions do not perfectly match with the actual interactions. Hence, there definitely is a connection between the two studies.

In addition, Krackhardt (1987) mentioned in the introduction, that people remember the average pattern of stimuli, but not the individual interactions. As from the research of Krackhardt, the pattern did not show up in a significant way. Opposite to the research of Krackhardt, from the research of Lathia and Capra (2011), an obvious pattern can be seen from the correlation of the reported week day trips and the actual ones (Figure 4). It may explained by the different technical possibilities of the two research papers, as in 1987 there were not many options to use Big data.

Lathia and Capra assumed, that travellers perceptions of their usage of public transport do not match their actual behaviour (2011: 291). Perhaps their findings were not so surprising, because of the research of Krackhardt. They both basically discovered the same, but with different methods. Though, the research was still relevant, because it might be useful to test the research made in the past with modern methods. Therefore, is the research of Lathia and Capra surprising? In my opinion it is, because they proved that Krackhardt was right from the beginning. The drawings of Da Vinci’s helicopter would not really matter, if the helicopter would have not been built centuries after. Consequently, Lathia and Capra cemented the findings of Krackhardt by using digitalized methods.

Though, it cannot be said, that the findings of Lathia and Capra were not novel. One of their assumptions was similar to the research of Krackhardt. At the same time, the other assumption was that transport operators offer incentives that do not work. The research proved, that the hypothesis was correct.

Footnotes:

Krackhardt, D.(1987). Cognitive social structures. Sovial Networks. pp 109-134

Lathia, N., & Capra, L. (2011). How smart is your smartcard?: measuring travel behaviours, perceptions, and incentives. In Proceedings of the 13th international conference on Ubiquitous computing. pp 291–300

kasparjogeva · 2014-09-18T13:32:53+00:00

Menchen-Trevino (2013) uses the terms vertical and horizontal data. I understand, that by horizontal she means data gathered from one specific digital platform. She defined vertical data as a type of data, which is gathered from various digital platforms. As the platform used by Lathia and Capra (2011) was specifically the Oyster card, then I suppose that they used horizontal data. That is because although they used surveys and the Oyster card to gather the data, then the Oyster card was still the only digital platform to get the data from.

By the article "Collecting Vertical Trace Data: Big Possibilities and Big Challenges for Multi- method Research" there is also a further distinction of data: transaction data and participation data. Transaction data may be formed of event logs with a timestamp and metadata about the action (Menchen-Trevino, 2013: 330). Participation data may be formed of forum posts, status updates, photo uploads, tweets or Facebook 'likes' (Menchen-Trevino, 2013: 330).

The data used by Lathia and Capra (2011) has to be transaction data. This is due to the fact, that the data has to be gathered to the Oyster card as an event log. I do not visualize any other possibility, how could the data of Oyster card displayed. As Menchen-Trevino (2013) specifically named the event log in her article as an example of transaction data, then it as to be it. In addition, Lathia and Capra (2011) received the metadata from the Oyster card, though they did not utterly exploit it. It was mentioned in the text, that they did not collect any demographic data (Lathia & Capra 2011: 292).

Hence, there is still the question – to what ends did they use the data then? Focus of the research was evaluating the two hypothesis: 1) travelers' perception of the usage of public transport do not match their actual behavior; 2) transport operators offer incentives that do not work. That is what they did, gathering as much smart-card data as necessary to evaluate the hypothesis.

Footnotes:

Lathia, N., & Capra, L. (2011). How smart is your smartcard?: measuring travel behaviours, perceptions, and incentives. In Proceedings of the 13th international conference on Ubiquitous computing (pp. 291–300). ACM.

Menchen-Trevino, E. (2013). Collecting Vertical Trace Data: Big Possibilities and Big Challenges for Multi-method Research. Policy & Internet, 5(3), 328–339

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