Month: november 2015

Disrupting access to scholarly journals III

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OK, part 3. Here is part 1 and part 2.
I made the rookie mistake of not following the ICanHazPDF etiquette: I did not provide a DOI for the article I requested.
No surprise – two weeks later, I have still not received a PDF.

This morning I tried again. Tweetdeck was supplied with a tweet containing the DOI, the hash-tag and my mailadress, and tasked to tweet at 9.00 AM local time.

9.03 my tweet was retweeted by @shecanhazpdf.

9.31 I recieved an e-mail with the subject “Yes, you can haz :)” – and the PDF. Please note: This is a paper that I have co-authored and that I have legal access to, through my work.

Where did it come from? Good question. The first rule of Fightclub is that you do not talk about Fightclub. Similarly, you do not reveal who fulfilled your request. Odds are that whoever helped me, is breaking a license agreement. The e-mailadress I got the PDF from is rather anonymous, but it is a good guess that the owner is a night elf hunter from the same timezone as Denmark. Not that it matters, but it would be interesting to hear what motivation there is behind the mail.

Anyway. Our Inter-Library-Loan department is quick, but probably not that quick. This was a test. The result is clear: Make your request in the proper way, and it is fulfilled in 30 minutes.

Is this going to disrupt the access to scholarly journals, provided by libraries?

While I’m waiting for a Twitter API-Key

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I’m working on a series of posts about the ICanHazPDF phenomenon. You can find the latest here. What I would really like to do, is to harvest tweets with the hash-tag, and analyze the data. That requires an API-Key from Twitter. And for some reason, that is a bit difficult.

Anyway, what other data could be interesting to harvest from social media sites? Data that would actually reveal things that are not common knowledge.

LinkedIn perhaps. If activity from persons employed at a given workplace was harvested – could that data, or rather changes in that data, be used to tell something about that place?

In other words: If the data was available, would we see an increase in activity from employees at The Royal Library after the latest cutbacks were announced?

And could trends like that be used to reveal when it would be a good idea to buy or sell stock in a company?

Mere web automatisering – LinkedIn og Twitter

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Hvordan får man automatisk trukket data ud om hvor mange følgere man har på Twitter?

Hvordan får man automatisk trukket data ud om hvor mange kontakter man har på LinkedIn?

<indsæt plidder-pladder om hvorfor det er vigtigt at have en tilstedeværelse på sociale medier og betydningen af hvor meget man har det og hvorfor nørder vil automatisere det ret kvantificerbare mål>

Med andre ord det skal ske automatisk. Hvordan?

Selenium to the rescue!

Og her er koden:

from selenium import webdriver
driver = webdriver.Firefox()
driver.get(“http://dk.linkedin.com/in/cbknudsen”)
content = driver.find_element_by_class_name(‘member-connections’)
print content.text
driver.close()

driver = webdriver.Firefox()
driver.get(“http://twitter.com/nusse”)
content = driver.find_element_by_class_name(‘ProfileNav-item–followers’)
print content.text
driver.close()

 

Man indsætter naturligvis de rette links til rette sider. Det her er dem jeg interesserer mig for. Der skal naturligvis suppleres med noget der fanger tallene. Lige nu får jeg følgende ud:

247
forbindelser
FOLLOWERS
44

Og jeg kan godt nøjes med de to tal. Der så skal sendes til et eller andet sted, og plottes og sådan.