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Exploring Social Media Search Results
1. Exploring Social Media Search Results
Rianne Kaptein
ECIR Industry Day
April 5th 2012 Barcelona
2. BACKGROUND OXYME
Fact Sheet Clients
Est. in 2007 Consumer Goods FMCG
Based in Amsterdam
24 client staff (9 nationalities) and 350 social
media analysts around the globe Chemicals
13 languages covered by native speakers Transport & Logistics
125 projects completed at:
Other sectors
Dutch National Airport
o 30 Multinational clients
o In 12 countries
Dutch National Railways
3. APPROACH | QUALITY DATA BY AUTOMATED & HUMAN ANALYSIS
Inhouse built Human analysis Translate high
specialized to remove not quality data into
search software relevant results actionable insights
Define a solid Collect opinions Smart analysis Classify only Analyze and
search strategy with a webrobot relevant data report
Total results WHERE
Search strategy WHAT
WHO
Search period # Not relevant
MESSAGE
Search terms SENTIMENT
And thousands
more! Etc.
# Relevant
5. 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”
6. 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
11. YET ANOTHER SEARCH ENGINE
•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
15. TWO DIMENSIONAL WORDCLOUDS
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"
17. WARNING SIGN 1
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
20. WARNING SIGN 2
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!
21. 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
22. CONCLUSIONS
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