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@LowAnimalSpirit twitter bot - tweeting live speculative headlines

The analysis produces new phenomena in the form of headlines generated with the help of Natural Language processing algorithms, tweeted @LowAnimalSpirit.

Low Animal Spirits by Ami Clarke and Richard Cochrane 2014.
Installation at Banner Repeater - with support from The Elephant Trust and ACE.

Low Animal Spirits by Ami Clarke and Richard Cochrane is an HFT algorithm driven by real time data, scripted as a live onscreen score and audio work with automated ‘readers’. Taking its cue from the oft-mentioned loss of the referent in both language and the economy, it is a live model of high frequency trading, dealing in words sourced from global news feeds for virtual ‘profit’, whilst speculating on their usage. The analysis produces new phenomena in the form of headlines generated with the help of Natural Language processing algorithms, tweeted @lowanimalspirit.

The visualization that is projected is a glimpse into the HFT algorithms buying and selling activity with volatility at the centre of these concerns.  It accesses 994 English Language global news feeds ‘live’ and acts upon the data as if it were trading in the global market place, analysing words in terms of the potential for a virtual ‘profit’ to be made.  You are watching what is about to trend, and likewise, the speculative headline generator is trying hard to anticipate the next headline, based on recent history, and incoming headlines, with the help of a Natural Language Processing algorithm.

The work address’ concerns relating to how algorithms curate big data, daily, and hence are reshaping knowledge production today.  It takes these ideas to an intensified degree via a High Frequency Trading algorithm – applying high speed algorithmic methods to the global production of news, it’s distribution and reception - and raises further concerns relating to the production of new knowledge, as a result.

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