Interest intensifies in Twitter-powered stock trading platforms

Interest intensifies in Twitter-powered stock trading platforms

Thanks to the development of the Social Web we are witnessing the emergence of new “massive-passive” data sets. Cynics shouldn’t be fooled by the humble nature of the base components within massive-passive data. When read in isolation any Facebook update, Twitter message, blog post or Geo-tag can seem quite banal. But when all of this activity is brought together and weighed in the balance something astonishing emerges.

It”s becoming widely recognised that massive-passive Social Web data generated by humdrum, everyday occurrences has a profound ability to reflect, in real-time, hidden patterns of relationship and behaviour in our society. Perhaps even more surprising is the related, and growing, body of evidence that suggests the same online ecologies can accurately predict (or at least pre-figure) the future of brands and markets.

For instance, recent papers by HP”s famous Palo Alto Labs demonstrate how Twitter data can be used to predict box office success for new movies. Other examples (such casino online as this and this) show how social media data can be used to predict the future of stocks. This isn’t science fiction or some kind of digital voodoo, but a natural outcome of the latest Network Analysis technology.

Dollywagon is intensely interested in this field. Our Influence Engine’s capabilities have developed rapidly over recent months and are now extracting exciting predictions about future market movements from a range of web-based data sources. For instance, the image below is derived from a recent analysis of around 10,000 news articles about the Market Research industry (we chose MR just because we’re familiar with it).

We used a computational language analysis (or N-gram) process to analyse this huge volume of web page content. The image is annotated and represents the final frame in a time-series animation (not shown) that reveals the underlying relationships between various ideas, knowledge and trends that underpin the behaviour and development of the Market Research industry.

A key feature of the analysis was an early indication of the eclipse of traditional full-service business models in the MR industry. This trend co-occurred with spectacular growth in the adoption of online research panels, which itself is being out-shone by the current rise of Social Web Analytics.

Early results suggest this approach to analysing both Twitter and other sources of web content show great promise for making good predictions about future market developments.

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