Social media brand analysis
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Copy the .brandelion config file to your home directory
~/.brandelion. Edit the config file to specify the output path and the Google Search API keys. The latter are only needed if you'll be fetching exemplars by keyword -- you'll need to also create a Google Custom Search Engine, enteringtwitter.comas the site to search. -
Create a list of brand Twitter accounts and store in
$BRANDELION/brands.txt.
$ cat $BRANDELION/brands.txt
7UP
100percentpure
18Rabbits
34Degrees
5hourenergy
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Collect followers for each brand (here, we limit to 100 followers per brand, for demonstration purposes).
$ brandelion collect --followers -i $BRANDELION/brands.txt -o $BRANDELION/brand_followers.txt -m 100 Fetching followers for accounts in /data/brandelion/brands.txt collecting followers for 7UP fetched 5000 more followers for 259370909 collecting followers for 100percentpure fetched 5000 more followers for 26286294 collecting followers for 18Rabbits fetched 1183 more followers for 29249985 collecting followers for 34Degrees fetched 1934 more followers for 80340314 collecting followers for 5hourenergy fetched 5000 more followers for 33666177 -
Collect tweets for each brand (here, we limit to 200 tweets per brand, for demonstration purposes).
$ brandelion collect --tweets -i $BRANDELION/brands.txt -o $BRANDELION/brand_tweets.json -m 200 fetching tweets for accounts in /data/brandelion/brands.txt Fetching tweets for 7UP fetched 199 more tweets for 7UP fetched 200 more tweets for 7UP Fetching tweets for 100percentpure fetched 200 more tweets for 100percentpure Fetching tweets for 18Rabbits fetched 198 more tweets for 18Rabbits fetched 200 more tweets for 18Rabbits Fetching tweets for 34Degrees fetched 200 more tweets for 34Degrees Fetching tweets for 5hourenergy fetched 200 more tweets for 5hourenergy -
Create a list of exemplar Twitter accounts. You can either do this manually, or use the collect script to search by keyword. E.g.,
$ brandelion collect --exemplars --query environment --output exemplars.txtwill search for accounts on Twitter Lists that match the keyword "environment". The output file stores how many distinct list this account appears on, which you can use to filter to the most common accounts.
Store the final list of exemplars in $BRANDELION/exemplars.txt
$ cat $BRANDELION/exemplars.txt GreenPeace EnvDefenseFund globalgreen OurOcean ClimateReality -
Repeat the follower and tweet collection steps above, writing to
exemplar_followers.txtandexemplar_tweets.json:$ brandelion collect --followers -i $BRANDELION/exemplars.txt -o $BRANDELION/exemplar_followers.txt -m 100 Fetching followers for accounts in /data/brandelion/exemplars.txt collecting followers for GreenPeace fetched 5000 more followers for 3459051 collecting followers for EnvDefenseFund fetched 5000 more followers for 20068053 collecting followers for globalgreen fetched 5000 more followers for 19409588 collecting followers for OurOcean fetched 5000 more followers for 71019945 collecting followers for ClimateReality fetched 5000 more followers for 16958346 $ brandelion collect --tweets -i $BRANDELION/exemplars.txt -o $BRANDELION/exemplar_tweets.json -m 200 fetching tweets for accounts in /data/brandelion/exemplars.txt Fetching tweets for GreenPeace fetched 200 more tweets for GreenPeace Fetching tweets for EnvDefenseFund fetched 200 more tweets for EnvDefenseFund Fetching tweets for globalgreen fetched 200 more tweets for globalgreen Fetching tweets for OurOcean fetched 200 more tweets for OurOcean Fetching tweets for ClimateReality fetched 200 more tweets for ClimateReality -
Collect tweets for a representative sample of accounts, stored in
sample.txt.$ cat $BRANDELION/sample.txt RedCross TobaccoFreeKids CFR_org Habitat_org PRI $ brandelion collect --tweets -i $BRANDELION/sample.txt -o $BRANDELION/sample_tweets.json -m 200 fetching tweets for accounts in /data/brandelion/sample.txt Fetching tweets for RedCross fetched 200 more tweets for RedCross Fetching tweets for TobaccoFreeKids fetched 200 more tweets for TobaccoFreeKids Fetching tweets for CFR_org fetched 200 more tweets for CFR_org Fetching tweets for Habitat_org fetched 200 more tweets for Habitat_org Fetching tweets for PRI fetched 200 more tweets for PRI -
Compute the social scores between the brands and the exemplars, based on network properties. (In this example, there is no follower overlap, so scores are 0.)
$ brandelion analyze --network --brand-followers $BRANDELION/brand_followers.txt --exemplar-followers $BRANDELION/exemplar_followers.txt --output $BRANDELION/social_scores.txt read follower data for 5 brands and 5 exemplars results written to /data/brandelion/social_scores.txt $ cat /data/brandelion/social_scores.txt 5hourenergy 0.000000 18Rabbits 0.000000 7UP 0.000000 100percentpure 0.000000 34Degrees 0.000000 -
Compute scores for each brand based on textual overlap with exemplars.
$ brandelion analyze --text --brand-tweets $BRANDELION/brand_tweets.json --exemplar-tweets $BRANDELION/exemplar_tweets.json --sample-tweets $BRANDELION/sample_tweets.json --output $BRANDELION/text_scores.txt read 5 exemplars, 5 brands, 5 sample accounts top 10 ngrams: york city=5 000 people=4 the planet=4 hashtagpeoplesclimate march=4 hashtagpeoplesclimate hashtagpeoplesclimate=4 marching for=4 hashtagactonclimate hashtagactonclimate=4 join the=4 climate action=4 our climate=4 $ cat $BRANDELION/text_scores.txt 7UP 0.053655 100percentpure 0.100966 18Rabbits 0.105482 34Degrees 0.086343 5hourenergy 0.090429