This document discusses using social network analytics to listen to customers and gain insights. It provides examples analyzing Twitter data about telecommunications companies in Greece and the US. Key topics and sentiment from the Twitter data are identified. Insights gained include large networks discussing social activities and advertisements while smaller networks discussed new products and technical problems. The tools and techniques described can provide competitive advantages through understanding customer needs, discussions, and satisfaction levels in the market.
isMOOD: Listening to the customers’ voice through social network analytics
1. Listening to the customers’ voice through social network analytics
Χρήστος Κουνάβης & Δρ. Διονύσιος Σωτηρόπουλος
15ο Συνέδριο InfoCom World
30/10/2013
2. The services
Social Network Analytics
Listen to the customer
Discover your market
Target your niche
Explore emerging opportunities
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5. Greek Case
ü Example on Twitter Analysis
ü Collecting Real Time twitter data (30/09/2013 – 12/10/2013)
ü Keywords: cosmote, vodafone_gr, wind_hellas
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7. Greek Case: Topic/Trend Detection
Topic #1
Keywords: πρωτοετείς, φοιτητές, προκήρυξη, υποτροφία
Sentiment per day
Tweets per day
7/29
“Προκήρυξη Υποτροφιών OTE-COSMOTE: Δώδεκα χρόνια δίπλα
στους πρωτοετείς φοιτητές: Είκοσι (20) υποτροφίες ύψους...
http://t.co/3o8ZEAxAC1”
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8. Greek Case: Topic/Trend Detection
Topic #2
Keywords: γρήγορα, πόσο, ξενερώνει, χώρα
Sentiment per day
Tweets per day
8/29
“Πιο γρήγορο από το 4G της COSMOTE είναι το πόσο γρήγορα
σε ξενερώνει αυτή η χώρα....”
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9. Greek Case: Topic/Trend Detection
Topic #3
Keywords: μόνο, γρήγορο, τελικά, πρωτογενές, νεοναζί
Sentiment per day
Tweets per day
9/29
“Tο μόνο πιο γρήγορο από το 4G της COSMOTE είναι τελικά η
κράτηση των νεοναζί... Και το πρωτογενές πλεόνασμα...”
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11. Greek Case: Topic/Trend Detection
Topic #1
Keywords: κέρδισε, διπλές, προσκλήσεις, αγώνα, εθνικής
Sentiment per day
Tweets per day
11/29
“Κέρδισε και εσύ διπλές προσκλήσεις για τον αγώνα της Εθνικής
από το @sport24 & τη @Vodafone_GR”
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12. Greek Case: Topic/Trend Detection
Topic #2
Keywords: iphone, καταστήματα, απίστευτο
Sentiment per day
Tweets per day
12/29
“Φήμες θέλουνε το iPhone 5S στα ράφια των καταστημάτων της
Vodafone, Παρασκευή 18/10”
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15. Greek Case: Knowledge based on the trends
Large network which discussed : Social activities, Advertisements
Small network which discussed : Social activities, New products
Limited network which discussed : Technical problems
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16. How?
ü Sentiment Analysis at the document, sentence, and aspect level.
ü Opinion Holder identification.
ü Opinion mining (find trends, trustworthy opinions, spam opinions, and fake reviews).
ü Social media analysis (Twitter, YouTube, Facebook, etc.) for product, brand, and people-related opinions.
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17. The tools
Beyond-SOTA machine learning algorithms providing superior performance and accuracy in:
ü Topic and group modeling
ü Text mining and summarization
ü Sentiment classification
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18. US Case
ü Example on Twitter Analysis
ü Collecting Real Time twitter data (11/02/2013 – 22/02/2013)
ü Keywords: at&t, verizon
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19. US Case: Sentiment Analysis
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20. US Case: Topic/Trend Detection
Topic #1
Keywords: commercial, kids, little, love, funny, new, guy
Sentiment per day
Tweets per day
20/29
“Nothing in this world is as precious as the kids in the AT&T
commercials. Nothing.”
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21. US Case: Topic/Trend Detection
Topic #2
Keywords: free, wifi, cloud, hate, customers, deal, offer, network
Sentiment per day
Tweets per day
21/29
“AT&T and WiFi provider The Cloud announce roaming
agreement http://t.co/39fR8LQV #WiFi @ATT #TheCloud by
@nirave”
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22. US Case: Topic/Trend Detection
Topic #3
Keywords: every, you, way, possible, single, person,
dear, frustrated
Sentiment per day
Tweets per day
22/29
“Dear AT&T I’m curious WHAT DID WE DO WRONG TO RECEIVE
SHITTY SERVICE”
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23. US Case: Sentiment Analysis
23/29
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24. US Case: Topic/Trend Detection
Topic #1
Keywords: phone, get, service, like, dont, fuck
Sentiment per day
Tweets per day
24/29
“This is why everyone needs VERIZON ! You’ll get service everywhere !”
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25. US Case: Topic/Trend Detection
Topic #2
Keywords: fios, lte, commercial, like, sale
Sentiment per day
Tweets per day
25/29
“I love FIOS actually, nvr had any prob with it knock on wood.”
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26. US Case: Knowledge based on the trends
Network which discussed : Advertisements, Support, Products
Network which discussed : Products, Network Infrastructure
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27. Gaining Competitive Advantage with Advanced Intelligence Tools
“How satisfied is my market?”
“What does my market need and discuss?”
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