Exploring Social Media Search Results
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Exploring Social Media Search Results
Rianne Kaptein
ECIR Industry Day
April 5th 2012 Barcelona
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BACKGROUND OXYME
Fact Sheet
Est. in 2007
Based in Amsterdam
24 client staff (9 nationalities) and 350 social
media analysts around the globe
13 languages covered by native speakers
125 projects completed at:
o 30 Multinational clients
o In 12 countries
Consumer Goods FMCG
Clients
Transport & Logistics
Dutch National Railways
Dutch National Airport
Chemicals
Other sectors
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APPROACH | QUALITY DATA BY AUTOMATED & HUMAN ANALYSIS
Collect opinions
with a webrobot
Smart analysis
Classify only
relevant data
Define a solid
search strategy
WHERE
WHAT
WHO
MESSAGE
SENTIMENT
Etc.
Total results
# Not relevant
# Relevant
Search strategy
Search period
Search terms
Analyze and
report
Human analysis
to remove not
relevant results
Inhouse built
specialized
search software
And thousands
more!
Translate high
quality data into
actionable insights
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The Problem
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SOCIAL MEDIA SEARCH TYPES
• Personal: What do my friends say about x?
• General: What does the world say about x?
• Commercial:
• What are people saying about my brand, product or campaign?
• What are people saying about my competitors?
Relevant result:
“Oh delicious! I just got Orangina at Albert Heijn. Orangina and I are friends for life”
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SOCIAL MEDIA SEARCH CHARACTERISTICS
• The date and time of search results is important.
• Out of the temporal context, the meaning of the message might be
lost
• The query can include temporal restrictions, e.g. monitor a product
launch
• Ambiguity of search terms
• Many search results are short such as tweets, or Facebook status
updates.
• Not a lot of noise in the text
• Recall is important, you want to know how many people talk about you.
• Large volumes of data
• You want to know who is talking and how influential their messages are.
• Identify promotors of your products
• Identify complaints
• Advertisements and spam
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TWITTER SEARCH RESULTS
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ICE ROCKET SEARCH RESULTS
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FINCHLINE SEARCH & MONITORING TOOL
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TuneIn
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•Goal: First impression about the buzz around a brand
•Exploit capabilities of human analysis: make it easy for the user to explore
and analyze the search results
•Show basic statistics
•Show differences over time
•Show all results: raise awareness about what people will find when they
search for your company
YET ANOTHER SEARCH ENGINE
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TUNEIN
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TUNEIN
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TUNEIN
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Two dimensions:
o Size of terms represents relative term frequency
o Colour of terms represents novelty of term
Instead of novelty other categorizations can be used as the second dimension
in the word cloud.
Categorizations can include :
• sentiment: positive vs. negative messages
• brands: messages mentioning "Braun" vs. messages mentioning "Gillette"
TWO DIMENSIONAL WORDCLOUDS
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POSITIVE VS. NEGATIVE COFFEE MACHINE MESSAGES
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Rubbish in, rubbish out!
Be careful with your categorizations.
If too many messages are not classified into the correct category, the quality of
the wordcloud will degrade.
Since in the interface it's easy to go back to the original message, users will not
trust the system if they see too many misclassified messages
WARNING SIGN 1
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COMPARING DELONGHI AND SAECO BY OCCURRENCES IN TEXT
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COMPARING TAGGED NEGATIVE POSTS SAECO AND DELONGHI
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Be careful with small result sets:
If at least one of the two categories only consists of a few messages (e.g. less
than 25) the statistics on which the wordclouds are based are not so reliable
Think about your minimum sample size!
WARNING SIGN 2
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OTHER POINTS OF ATTENTION
• Words can have multiple meanings
• Be clear on the fact it is an automatically generated summary
• Heavily retweeted messages can have a large influence on the wordcloud
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Wordclouds are a great search interface element for social media search
• Navigational aid:
Easy drilldown on search results
• Summary of large number of search results
Short, to the point messages
CONCLUSIONS
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www.oxyme.com
Cronenburg 150
1081 GN Amsterdam
tel: +31 20 625 000 5
e-mail: [email protected]
Thank you!