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Data was analyzed by manual content analysis.
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However, manual content analysis and classification of large numbers of photographs is time consuming.
We used manual content analysis to analyse the free-text answers.
Manual content analysis was performed of 13 780 tweets (figure 1).
Manual content analysis was used to categorise data under emerging themes.
Major and minor themes were identified through manual content analysis of the transcripts, and differing interpretations were discussed in order to reach consensus.
The data were analysed using a thematic approach following a path of familiarisation with the data, construction of a preliminary coding scheme, followed by manual qualitative content analysis and interpretation using a method adopted from Graneheim and Lundman [ 30].
As a first step to close this gap, Castán Broto and Bulkeley mapped 100 municipal climate action experiments by applying quantitative content analysis that required manual screening and coding of text data [26].
Analysis of data was done by using content analysis which consisted of reading and re-reading the text, manual coding in the margins, and through memos, synthesizing and grouping of data in relatively exhaustive categories [ 7].
The wording of the preferences formulated by people with ID and the criteria in the manual were analysed (content analysis) [ 17].
Analysis was by manifest content analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com