{"personalEmailAddress":"s.j.concannon@gmail.com","universityEmailAddress":"shauna.concannon@ncl.ac.uk","description":"The data provided includes the User reviews from FeedFinder, together with Index of Multiple Deprivation (IMD) data associated with the venue location. This was created by cross referencing the postcode with the publicly available IMD data (Text_review_IMD_Decile.csv). 2) Detailed breakdown of IMD data for each review(venue_review_data_detailed.csv). I have also included the full output from the IMD, which includes a breakdown of each of the constituent factors which collectively inform the IMD overall rating  3) LDA topic weightings for each review, together with the hand coding annotation for privacy and designated areas (ff_data_LDA_topic_weighting_Priv_DA_Coding.csv) 4) Original outputs from topic models produced using MALLET implementation of LDA for 30 topics which are described in the paper and used for the analysis: Original input - malletQuintFF.txt; Mallet Composition - malletQuintFF.mallet_composition30.txt; Mallet keys - malletQuintFF.mallet_keys30.txt","toolsUsed":"The data was collected via the FeedFinder mobile application. The data is volunteered by users who interact with the app to leave reviews about their experiences of breastfeeding in public spaces. Data froth app is stored in an SQL database, from which the data presented here was extracted, before being cross-referenced with the IMD data associated with the postcodes of the venue locations.","collectionDateRangeStart":"05\/2013","collectionDateRangeEnd":"01\/2017","geographicCoverage":"UK","validationMethod":"The initial step was to prepare the data for analysis, and integrate our VGI data, and in particular the review comments, with the associated data from the IMD. Using the geocoded data associated with each review venue, the data was cross-referenced with the IMD. The IMD decile for each venue location was established using the Lower-layer Super Output Areas (LSOA), neighbourhoods with populations <1500, and IMD rank data to provide contextual information on the relative deprivation of the location. This facilitated an analysis of the textual data that could be then positioned in dialogue with an officially created dataset on contextual factors of deprivation. 2727 user reviews were included in the final dataset for analysis (717 entries were excluded on the basis that they featured no comment data or because a postcode match was not generated, resulting in no associated IMD data).","secondaryOverview":"Information on the IMD available online at: https:\/\/www.gov.uk\/government\/statistics\/english-indices-of-deprivation-2015","publicationTitle":"Applying Computational Analysis to Textual Data from the Wild: a Feminist Perspective","definitions":"UUID - unique Identifier; TEXT - review text; soa_id -  super output area ID (see IMD website for details)","variableExplanation":"-","missingData":"-"}