social media campaigning@gold

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Week 4

This week was about mapping.

Obviously the biggest online map is Google Map but it has many controversial elements. For example when Google goes around by the 360 degrees special camera vehicle for Google Street, it also collects Wifi connection data. What the company wants by providing the map service is more precise people’s personal data. They want data of what people are interested in who live in a particular area.

There is an open source map called Open Street Map. It’s a wikipedia mapping.

There is no copyright so you can use it in whatever way you want.
You can also modify it far more freely than Google Map.

I actually knew about it and tried it again but I don’t think I’m going to use it as a primary mapping tool, personally Google Map is more sophisticated, it has shop names, route search and it’s faster. The reason why I think Google Map is better is its capital. They earn lots of money therefore they can invest more in their services. If their services were too open, they would be unable to earn that much money. There is a huge contradiction here. People normally have to work on open source projects in their spare time for nothing. On the other hand Google has well paid elite engineers. In order to keep having them, Google has to monetise their services. However I actually just remembered that Google also let people do work for them for almost nothing, for example, jobs walking around mountains carrying the Google Street camera. Perhaps it’s again the Internet’s law of the first one becomes the biggest there for the best, just like Amazon. As everyone uses Google Map, Google has the most data therefore they can make the best map. The word “best” here means the preciseness of the map. Google Map has shop names etc but Open Street Map doesn’t.

Mapping can have massive power, for example, revealing where prisons are in a country where that information is hidden.

We tried Google Fusion Table.
I made this Wiki page on social media campaigning wiki.

How to use Google fusion tables for mapping locations
Jump to: navigation, search

1. log into Google drive
2. find a spread sheet
3. copy it and paste to a spread sheet
4. open Google fusion tables
5. import the spread sheet created
6. go to “row 1”
7. change the location column to “location”
8. “add map”
9. complete


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Week 3

This week the lecture’s focus was crowdsourcing. Crowdsourcing is not only about the web but also generally about how things should be done.

Dan briefly talked about charity organisations such as Red Cross. As soon as a big disaster happens, the first one to go help the site is always Red Cross. It was the same when the big earthquake happened in Japan in 2011. The main donation detonation advertised on TV was Red Cross. Many people wanted to do something for the victims so everyone made a donation to them. I didn’t as I knew the money was not going to be spent for immediate actions. It was true and the money donated to Red Cross was later bureaucratically distributed among each prefecture, each city/town/village and then each victim. This process took so long and the money was not spent for independent volunteers or organisations.

Dan said those big charity organisations such as red cross often behave as though they have some sort of copyright or patent for their activities. They want to use catastrophes as opportunities for fund raising.

The purpose is different but an alternative way of doing things was introduced by Dan, and that was “Let’s do it!”.

It originates in Estonia and it’s a kind of cleaning mob, meaning many people assemble at somewhere on a certain date and do a massive cleaning together. In Estonia everyone talks about how beautiful their nature is but weirdly people cannot stop throwing away stuff to the environment.

This way of doing things is much quicker but there is a problem. Why can the government or council not do it instead of them? They already receive taxes from citizens so they should do it instead. However they are indeed bureaucratic and very slow. An attempt like Let’s do it! can prove that the government is totally capable of doing things which they say they cannot do. It also allows people to actually do stuff for change rather than just complaining.

However the biggest challenge for those attempts is how you carry on after a success. You have to decide whether you will let the government do this or get some funds from the government and keep doing it by yourselves.

We then started to look at various crowdsourcing websites such as Samasource and CrowdFlower. I actually already knew about both of them. I once did a massive online research about micro-labour and found those websites alongside of Amazon Mechanical Turk and Bitcoin Get.

Bitcoin Get is actually based on CrowdFlower and I did three tasks before. What I did was to search certain keywords on Google and see what number the specified websites are displayed from the top. I had to actually go to the website and copy particular information from the website and paste it on the CrowdFlower window. There are always verification processes for those tasks. Dan explained about how these crowdsourcing systems work without CVs or proving skills. They let a number of people do the same task and get the average answer for it.

Here is the patent for CrowdFlower.

As far as I know Amazon Mechanical Turk works in a bit different way, some tasks require certain skill levels and you need to pass the tests to do them. Mozilla also does a free online qualification badge service, if you pass a test, you can get a badge for the skill and use it to prove your skill on other websites.

We then did a discussion about the definition of crowdsourcing. What is it exactly? We talked about the difference between crowdsourcing and outsourcing. Amazon Mechanical Turk or Bitcoin Get is certainly more like outsourcing. Crowdsourcing should be more about learning, for example like Crop Mob.

With CropMob people assemble at a farm to learn how to grow crops together.

Dan however said it’s also like a massive unpaid internship. It’s true…

The Iranian government tried to find a particular demonstrator and found him using the crowd power of the Internet.

In my opinion, this is more like crowd bullying. It’s similar to when someone uploads a picture of doing an illegal activity, it goes viral, the person’s profile is revealed and the person has to pay the serious price for what s/he has done. There is also a similarity between CropMob and flashmob.

Our conclusion was crowdsourcing should involve some sort of motivation and people should be able to learn something out of it. From my experience, Bitcoin Get’s tasks are so boring and you cannot learn anything from it except for how the system works.

Dan then talked about Kick Starter briefly. The key to success on Kick Starter is to make a cool video. In my opinion, this is a huge problem. “Cool video = success” means only cool people can succeed. Dodgy yet good projects will never get funded.

Dan also talked about the difficulty of the production based on Kick Starter, he said if you try to deliver products to a large number of people, you cannot help falling into the normal mode of factory production. So Kick Starter would not become a new mode of production.

We then tried Etherpad as a crowdsourcing/micro-labour experiment.

Etherpad allows a number of people to edit a note pad simultaneously in real time.

We split into groups and wrote about the verification methods for tweets, images, videos and events on a map.

At the end we learned exif, metadata of photo files.

I actually did a small experiment, checking whether resizing on Gimp can delete exif or not.

The original photo’s exif data according to




Model NIKON 1 J1

Aperture 3.5

Exposure Time 1/60 (0.0166666666667 sec)

Lens Spec 10-30mm f/3.5-5.6 VR [4]

Focal Length 10.0 mm

Flash No Flash

File Size 5.7 MB

File Type JPEG

MIME Type image/jpeg

Image Width 3872

Image Height 2592

Encoding Process Baseline DCT, Huffman coding

Bits Per Sample 8

Color Components 3

X Resolution 300

Y Resolution 300

Software Ver.1.20

YCbCr Sub Sampling YCbCr4:2:2 (2 1)

YCbCr Positioning Co-sited

Exposure Program Not Defined

Date and Time (Original) 2013:10:26 17:44:53

Max Aperture Value 3.5

Metering Mode Multi-segment

Light Source Unknown

Color Space Uncalibrated

Sensing Method One-chip color area

Custom Rendered Normal

Exposure Mode Auto

White Balance Auto

Digital Zoom Ratio 1

Focal Length In 35 mm Format 27 mm

Scene Capture Type Standard

Gain Control High gain up

Contrast Normal

Saturation Normal

Sharpness Normal

Subject Distance Range Unknown

Quality Fine

F Number 3.5

Exposure Compensation N/A

Focus Mode AF-A

Flash Mode Did Not Fire

ISO 2500

Compression JPEG (old-style)

Orientation Rotate 270 CW


[Resized version]

File Size 218 kB

File Type JPEG

MIME Type image/jpeg

Image Width 1000

Image Height 1494

Encoding Process Baseline DCT, Huffman coding

Bits Per Sample 8

Color Components 3

X Resolution 72

Y Resolution 72

YCbCr Sub Sampling YCbCr4:4:0 (1 2)

I was right!!!!!!

I tried with another photo taken on an iPad mini.



Make Apple

Model iPad mini

Aperture 2.4

Exposure Time 1/20 (0.05 sec)

Focal Length 3.3 mm

Flash No flash function

File Size 1816 kB

File Type JPEG

MIME Type image/jpeg

Image Width 2592

Image Height 1936

Encoding Process Baseline DCT, Huffman coding

Bits Per Sample 8

Color Components 3

X Resolution 72

Y Resolution 72

Software 6.1.3

YCbCr Sub Sampling YCbCr4:2:0 (2 2)

YCbCr Positioning Centered

Exposure Program Program AE

Date and Time (Original) 2013:11:06 13:23:22

Metering Mode Multi-segment

Color Space sRGB

Sensing Method One-chip color area

Exposure Mode Auto

White Balance Auto

Focal Length In 35 mm Format 33 mm

Scene Capture Type Standard

F Number 2.4

ISO 250

Compression JPEG (old-style)

Orientation Rotate 90 CW


[Resized ver]

File Size 279 kB

File Type JPEG

MIME Type image/jpeg

Image Width 1020

Image Height 1365

Encoding Process Baseline DCT, Huffman coding

Bits Per Sample 8

Color Components 3

X Resolution 72

Y Resolution 72

YCbCr Sub Sampling YCbCr4:4:4 (1 1)