%0 Generic %A Gorrell, Genevieve %A Maynard, Diana %A Bakir, Mehmet %A Kanai, Juan %A Temple, Luke %A Harrison, Jacqueline %A Bontcheva, Kalina %D 2020 %T BA Brexit Geomedia Shared Data %U https://orda.shef.ac.uk/articles/dataset/BA_Brexit_Geomedia_Shared_Data/12287498 %R 10.15131/shef.data.12287498.v1 %2 https://orda.shef.ac.uk/ndownloader/files/22646531 %2 https://orda.shef.ac.uk/ndownloader/files/22646534 %2 https://orda.shef.ac.uk/ndownloader/files/22646537 %2 https://orda.shef.ac.uk/ndownloader/files/22646540 %2 https://orda.shef.ac.uk/ndownloader/files/22646543 %2 https://orda.shef.ac.uk/ndownloader/files/22646546 %2 https://orda.shef.ac.uk/ndownloader/files/22646549 %2 https://orda.shef.ac.uk/ndownloader/files/22646552 %2 https://orda.shef.ac.uk/ndownloader/files/22646555 %2 https://orda.shef.ac.uk/ndownloader/files/22646558 %2 https://orda.shef.ac.uk/ndownloader/files/22646561 %2 https://orda.shef.ac.uk/ndownloader/files/22646564 %2 https://orda.shef.ac.uk/ndownloader/files/22646567 %K Twitter %K Brexit %K Media %K Newspapers %K Geography %K Internet %K Politics %K Social and Community Informatics %K Human Information Behaviour %X This archive contains shared materials pertaining to the forthcoming paper "Local media and geo-situated responses to Brexit: A quantitative analysis of Twitter, news and survey data" by Genevieve Gorrell, Mehmet E. Bakir, Luke Temple, Diana Maynard, Jackie Harrison, J. Miguel Kanai and Kalina Bontcheva.

It contains a folder with a separate document for each of the topic-model-derived topics explored in the paper. The first two columns are topic scores for material from each separate Twitter account in the corpus, along with their Brexit vote intention. After a blank column comes the national newspaper article topic scores. After a further blank column come the local newspaper article scores, along with the NUTS1 region in which they are published.

Additionally there is a spreadsheet with entity-based topic scores for each newspaper.

Ethics approval was obtained for the Twitter data collection from the University of Sheffield (application number 011934).
%I The University of Sheffield