Month: June 2011
I suppose that highest aspiration of an author is to get a phone call early one morning from an English speaking person with a heavy Swedish accent. The second highest may be to become an adjective such as “Shakespearian”. Now young suburbian observer Lone Aburas (her last letter is not indicating genitive) has managed to become an adjective just after her second novel. Congratulation!
The novel is called Den svære toer, – The difficult second, i.e. second book.
Collective novel with modern social realism detailing depressing everyday life of suburbians. Not a winner? Well, the book is loaded with sufficient Danish humor and irony that we well manage. One blogger writes he has a difficulty in seeing the humor in the novel. Sorry for him. Lone Aburas clearly states that she uses irony and the use of meta-commentary was humorous. Even the title was humorous: “[…] I think it was funny […] it is mostly an ironic title […]”. The ironic meta-commentary in the beginning and the end has the clearest scoops in this direction. The end sets up tasks for the reader. The reader may, e.g., “analyze the begining of the novel” and find examples of were the author breaks the rules that she sets up. This is meant ironically, so the reader should not necessarily do that. However, the reader may already have analyzed the beginning while reading it and found out that it was ironic (the beginning). As the rules set up were meant ironic, it means that these rules were not really set up and we expect the rules to be broken, meaning that the meta-rule is that the rules are to be broken. (The obvious next step for me here would be to come up with some meta-humoristic irony in a comment to the meta-humoristic irony of Aburas. I will not do that though)
Humor with irony sits centrally in Danish popular art: Hans Christian Andersen’s fairy tales, double entendre Barbie Girl of Aqua, humorous text of long-time popular Danish music group Shubidua (selling more records than the population of Denmark). Most best selling Danish film in Denmark in the last 40 years are comedies: Olsen Gang, Den eneste ene, Italiensk for begyndere and Klovn – the movie. Even Albert Speer-lover Lars Trier most popular work in Denmark is humorous.
But apart from the irony what does the novel wants? Not clear. Lone Aburas leaves her poor characters to their own destiny with divorce and a dog training course. In the Danish hit comedy Italian for beginning we also follow Copenhagen suburbians through a course. But this course in the Italian language ends successfully with a romantic trip to Italy while Lone Aburas dog training course ends with course participants being cheated for the course fee paid up front. Not nice.
On the negative side I also find that the novel lacks an index. The punctuation I find ok though.
Advices for Lone Aburas for her third novel? Well, more structure I would say. And action! Most modern literature involves one or possible a connected series of murders, – a case to solve. A revised second edition could, e.g., consider changing the police stop on page 126 with a dramatic car hunt. Also the car crash on page 134 could be described in detail. Another issue is what she herself acknowledge on page 137 with the words: “Actually I do not like to describe two humans having sex” which is a problem as she further writes “[…] you are not a real writer if you are not capable of writing about erotics”. She needs to work on that bit. Include murder and sex. Possible also international crime and the revolution in Egypt.
I have previously blogged about the Milena Penkowa case that has entertained the Danish research community in the first half of 2011. If you want an English update there is an overview in the April article Penkowa for dummies.One of the latest to jump on the wagon for Penkowa bashing is geologist Peter Riisager. Back in March he looked on the self-citations of Penkowa and reported it on his blog. He found that 54% of Penkowa’s citations where her own. The story was picked up a couple of weeks ago by the university newspaper Danish and English as well as a Danish science web-site. When Riisager finding that Penkowa has over 50% self-citations he links to a Nature blogger that claims that “Bad guys have > 50% self-citations” and “good guys have self-citations as < 50% of total cites (I [Brian Derby] am at 25%)”. qed: Penkowa is a bad guy. But is Riisager (and blogger Brian Derby) right? I cannot find out which method he used. 50% self-citations sounds fairly much. How can we investigate this further? Well, here is my methodology: I use ISI Web of Science, search on an author, press “Create Citation Report” to get number of articles the author has written (“Results found”) and the number of citations (“Sum of the Times Cited”), For the number of non-self citations I press “View without self-citations” and read off “Result: ” in the upper left corner of the web-page. Is that an ok procedure? Nah. I think the problem is that “Sum of the Times Cited” refers to the number of citations while “View without self-citations” refers to the number of papers with citations without self-citations. What we should (also) do is to get the number of papers with citations (“View Citing Articles”). The problem is that there are multiple citations in each paper. What we also would like to have is the number of citations without self-citations, but I don’t know how to get that number from ISI Web of Science. Below I have attempted a count on Milena Penkowa, Peter Riisager, myself and big shot neuroimaging analyzer Karl J. Friston. The “self-citation rate (A)” is computed what I believe is the wrong way (citations-Papers with non-self citations)/citations, while “self-citation rate (B)” is computed by the number of citing papers (Papers with citations – Papers with non-self citations)/Papers with citations.
|Author||Papers||Citations||Papers with citations||Papers with non-self citations||Self-citation rate (A)||Self-citation rate (B)|
(2012-03-07: language correction)
I have previously blogged about sentiment analysis. Code for simple sentiment analysis with my AFINN sentiment word list is also available from the appendix in the paper A new ANEW: Evaluation of a word list for sentiment analysis in microblogs as well as ready for download. It might be a little difficult to navigate the code, so here I have made the simplest example in Python of sentiment analysis with AFINN that I could think of.
(2012-12-01: Updated link to new gist at github)