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'Big Data'

From Big to Small Data in Search Engines

The next speaker at the CCC Symposium is Christina Lioma, whose focus is on search engines. These, too, are repositories of data, but contain unstructured, heterogeneous, and noisy data - we're using them to find needles in haystacks (using various search logics, in fact: known needles in known haystacks, unknown needles in unknown haystacks, etc.). The discipline of information retrieval aims to develop theoretical principles for modifying and quantifying information and topical relevance.

Doing 'Big Data' Twitter Research

My own paper started the post-lunch session at the CCC Symposium, discussing our Mapping Online Publics work in the field of Twitter research. I'll post up the slides and audio properly as soon as I can!

Slides and audio are below:

Making 'Big Data' Manageable

The next speaker at the CCC Symposium is Rasmussen Helles, who takes us back to the problem of 'big data'. Such data lend themselves well to visualisation, but this also creates substantial new problems as we make sense of data through their visual representations: we may see the patterns in the data, but we still don't necessarily know what they mean.

Big (and Small) Data in Context

The next speaker at the CCC symposium is the fabulous Nancy Baym, who begins by noting how overwhelming the buzz about 'big data' has become. There's a great deal of fascination just with the things we can do with big data sources - tracing interesting patterns, attempting to predict future processes, making sense of data by using algorithmic tools.

Data, Metadata, Big Data?

I'm spending the day at the Centre for Communication and Computing at the University of Copenhagen, where Klaus Bruhn Jensen has brought together a bunch of AoIR folks, including myself, for a one-day symposium called "Digital Data - Lost, Found and Made". I'll be speaking about our Twitter research in the afternoon.


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