The collection and analysis of microtexts is both straightforward from a computational viewpoint and complex in a scientific perspective, as they are accompanied by a profusion of metadata. We present and discuss an experimental setting to observe language through the lens of tweets, with a particular emphasis on the impact of querying and visualization techniques in time and space.
@InProceedings{BARBARESI18.16, author = {Adrien Barbaresi and Antonio Ruiz Tinoco}, title = {Using Elasticsearch for linguistic analysis of tweets in time and space}, booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {may}, date = {7-12}, location = {Miyazaki, Japan}, editor = {Piotr Banski and Marc Kupietz and Adrien Barbaresi and
Hanno Biber and Evelyn Breiteneder and Simon Clematide and Andreas Witt}, publisher = {European Language Resources Association (ELRA)}, address = {Paris, France}, isbn = {979-10-95546-14-6}, language = {english} }
Summary of the paper