NCCMA All Ears

Project Overview:

In this project Decoy performed an analysis of Facebook pages for ‘Save Lake Eppalock’ and ‘Friends of Lake Meran’ for the calendar year. The analysis identified posts and subsequent responses relevant to the broad topic of environmental water. The results were presented using summary tables (one for each interest group). Examples of posts were also provided. The selected posts were grouped around broad themes (e.g. water levels; weather and climate) and illustrate both positive and negative comments and the strength of emotion displayed.

Approach:

The Decoy team began by sampling a small number of posts for each interest group for each quarter in 2016. The aim was to gain understanding of the range of topics, post frequency and engagement with posts through comments. After this familiarisation process was complete, the team prepared an initial coding framework so that summary data for all relevant posts (those related to environmental water) could be entered in an excel spreadsheet post-by-post. Data entry for each post began with the post date (i.e. to assess frequency per month). The coding framework included a number of other topics (e.g. the post theme; the objective of the post; whether the post reflected a negative or positive view about that theme; and the level of emotion displayed). Sub-categories were also employed where applicable. For example, to describe the level of emotion displayed (where the options were neutral, somewhat emotional or highly emotional).

Approach:

The Decoy team began by sampling a small number of posts for each interest group for each quarter in 2016. The aim was to gain understanding of the range of topics, post frequency and engagement with posts through comments. After this familiarisation process was complete, the team prepared an initial coding framework so that summary data for all relevant posts (those related to environmental water) could be entered in an excel spreadsheet post-by-post. Data entry for each post began with the post date (i.e. to assess frequency per month). The coding framework included a number of other topics (e.g. the post theme; the objective of the post; whether the post reflected a negative or positive view about that theme; and the level of emotion displayed). Sub-categories were also employed where applicable. For example, to describe the level of emotion displayed (where the options were neutral, somewhat emotional or highly emotional).

Results:

The Decoy team identified 431 posts for ‘Save Lake Eppalock’ (322 relevant) and 105 posts for ‘Friends of Lake Meran’ (54 relevant) for the 2016 calendar year. There were 36,124 responses to posts for Save Lake Eppalock’ (33,230 relevant) and 1,710 responses to posts for ‘Friends of Lake Meran’ (1,550 relevant). Two tables were used to summarise the data from the responses to posts. The responses could be “likes”, “comments” and “shares”. The two tables include an assessment of the extent the comments supported or opposed the original post topic (i.e. using the options of disagree, unsure/not relevant,agree). To make sense of the large data set, posts were grouped according to broad themes. The two tables provide a summary of post and responses by theme. Examples of posts are also provided and these are grouped under the theme headings.

NCCMA All Ears Social Research

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