I have been trying to get a book off the ground for a couple of weeks. I don’t want to give too much away but it will (I hope) be about who has access to knowledge and for what purpose. Its a book that I have been planning in my head for a while. Problem is that it doesn’t sit neatly into a theme of academic publishing, it sort of sits between themes. Therefore getting the proposal to the right editor at the right publisher is proving difficult.
This was an interesting paper that I contributed a section too. It was a look back, and in a sense, a look forwards at four leading management studies journals, ASQ, JMR, JMS and HRM. My involvement was to look at the changing content of the journals in terms of the frequencies of the words being used. Even just looking at the words we were able to separate papers to their publishing journal, and when displayed as a network of correlations papers tended to cluster into journals. This is interesting as it does indicate that journals do have a house style that people inevitably conform to. The causality of how this happens is not clear, it could either be that journals influence how people write, or that people writing about similar things just tend to use similar words and then publish in a sub-set of journals. Further more we where able to look at the changing word use in a single journal through time. Again we were able to see that papers published in different periods of time tended to be most closely related to each other. The full paper is available online, and there is a poster looking at the data also linked below.
I intend to pick this work up again in the near future.
As part of my work exploring the notion of tipping points I did some work looking at abstract models of populations of Banks. This work actually follows on from earlier work (soon to be published in the Journal of Business History) looking at the development of the British Banking sector. It takes a look, through modelling and simulation, at how the banking sector might have developed had history been different ,while trying to contribute to the debate around what a tipping point is and can it be modelled. Modelling tipping points is difficult because the moment you decide that that is what you are doing, then you have already biased your work. You will inevitably build something that is at least capable of undergoing a tipping point. This paper attempts to explore this problem though the lens of banks. Full text, Bursting a Bubble: Abstract Banking Demographics to Understand Tipping Points?
In September 2013 at the British Science Festival we did some experiments with students from local schools. The idea was to get them thinking about how information and idea spread through populations of people. This could be anything from fashions to rumours and gossip. The experiments had a visual element as the student could see on a projected screen how the network was developing through time. We also mixed things up a bit to make them think about how information might spread if there was an incentive to being one of the majority. It was good fun and I think the students got something out of it. The full article for the Conversation can be read here.
A new paper is out (PLoS One so free to all), lead by Alberto Acerbi (Bristol Uni), and co-authored by Vasileios Lampos (Sheffield uni), myself (Durham Uni) and R. Alexander Bentley (Bristol Uni). Its a really fun paper looking at the changing pattern in the use of emotion words in the English language during the 20th Century. We make use of Google’s Ngram data. Google scanned approximately 4% of all books and generated a dataset of yearly world frequencies. We mined this dataset to extract the changing frequencies of emotion words throughout the 20th century.
In the data we can see the frequency of words expressing emotions such as anger, fear, joy, sadness, and disgust changing in line with historical events. Large social/cultural events like the World War II, the roaring 20s and the swinging 60s all show up as frequencies changes of words. Interestingly the World War I doesn’t seem to appear in the data, however the Great Depression in the 1930s does. We also expected, due largely to cultural stereo typing, that US books would be more emotional that UK. This is supported by the data, but the split occurs much more recently than we thought it might. Generally throughout the 20th century the frequency of emotion words has been declining, with one exception, fear. Could that be linked to the climate of fear that has developed during the latter half of the 20th century?
The paper has been really well received in the media, Alberto was interviewed for BBC Radio 4s Material World by Adam Rutherford. Alex and myself were interviewed for NPR.
New google ngrams paper it coming soon! It should be the start of a productive few months paper wise.