How the conversations about gastronomy in the 4 countries are compared in term of: • trend and volume • distribution of user locations • social network analysis • topics (hashtags) • most popular visual representation • emotion analysis • demography analysis

1. SOCIAL MEDIA ANALYTICS FOR
GASTRONOMIC
TOURISM
(INDONESIA, THAILAND, MALAYSIA,
AND VIETNAM)
Ismail Fahmi, Ph.D.
Director Media Kernels Indonesia (Drone Emprit)
Lecturer at the University of Islam Indonesia
Ismail.fahmi@gmail.com
Y-BIS ISI WEBINAR
11 FEBRUARY 2021

2. 2
1992 – 1997 Undergraduate, Electrical Engineering, ITB, Indonesia
2003 – 2004 Master, Information Science, University of Groningen, NL
2004 – 2009 Doctor, Information Science, University of Groningen, NL
2009 – Now Engineer at Weborama (Paris/Amsterdam)
2014 – Now Founder PT. Media Kernels Indonesia, a Drone Emprit Company
2015 – Now Consultant at Perpustakaan Nasional, Inisiator Indonesia OneSearch
2017 – Now Lecturer at the IT Magister Program of the Universitas Islam Indonesia
Ismail Fahmi, S.T., M.A., Ph.D.
Ismail.fahmi@gmail.com

3. AGENDA
• About Us
• Data Explosion
• Research Questions and Methodology
• Comparing the Social Media Conversation on Gastronomy Tourism
in Indonesia, Thailand, Malaysia, and Vietnam
3

4. ABOUT MEDIA KERNELS

5. THE MINISTRY OF COMMUNICATION AND
INFORMATION, INDONESIA
5

6. THE WEST JAVA PROVICE COMMAND CENTER
6
Drone Emprit
Drone Emprit Customized

7. SOCIAL MEDIA AND DATA EXPLOSION

8. DATA GROWTH: UNSTRUCTURED DATA
8

9. BIG DATA – SOCIAL MEDIA
9

10. 10

11. 11
MILLENIAL
GEN Z

12. SOCIAL MEDIA IMPACT ON GASTRONOMY
• The food and beverage industry is
the most volatile sector, which is
affected by the slightest shift in
customer preferences and needs.
• Earlier people trusted advertisers,
then, they trusted people and relied
on the interactions that take place
on social media.
• Customers express their views and
concerns on social media.
• This makes social media powerful
enough to have the potential to
move commodities and change
prices.
12

13. WHY GASTRONOMY INDUSTRY NEED SOCIAL
MEDIA ANALYTICS?
• The growing data-driven culture in the food and beverage
industry is helping to improve productivity. People are already
generating 2.5 quintillion bytes of data each day, and its analysis
is fostering growth.
• The needs of the food industry and the challenges they are
facing:
• Inability to gather vast data and make informed decisions.
• Inability to understand customer sentiments.
• Lacks consistent food quality.
• Road to success:
• Understand brand perception.
• Identify customer needs and fuel production ideation.
• Creative content strategy and campaigns.
• Optimize all your campaigns.
• Improve customer experience.
• Collaborate with influencers.
• Monitoring product launches.
13

14. FOODS DI INSTAGRAM
14

15. RESEARCH QUESTIONS
AND METHOD

16. RESEARCH QUESTIONS
• How the conversations about gastronomy in the 4 countries are compared
in term of:
• trend and volume
• distribution of user locations
• social network analysis
• topics (hashtags)
• most popular visual representation
• emotion analysis
• demography analysis
16

17. METHODOLOGY
17

18. SYSTEM ARCHITECTURE
18
News Crawler
Twitter Crawler
Twitter Streaming
FB Page Crawler
Data Pipeline
Data
SOLR Indexer 1 SOLR Indexer 2 SOLR Indexer 3 SOLR Indexer 4
Hadoop Framework
Physical Hardware
Insight
Data
Ingest
Management
&
Queue
Realtime
Job
Processing
Google Custom
Search
Database Framework
Scheduled
Job
Processing
Map Reduce
Sentiment
Analysis
Other
Processings
Data
&
Workflow
Management
Access
Visualization
Other sources
Analytics UI

19. MEDIA KERNELS FEATURES
19
Trends
DASHBOARD
Comparison
Topic Map
NEWS PORTAL
Latest News
Media
ANALYTICS
News Sites
Page Ranks
Sentiment Analysis
PF-Chart
Engagement
Exposure
Retweets
TOPICS
Replies
Most Shared URLs
Most Shared Videos
Topic Map
Word Cloud
Impact
INFLUENCERS
Engagement
Reach
Most Engaged
Followers
Influencer Network
SNA
Topic Network
PR-Values
Reach
Hashtags Posts
Bubble Map
Twitter User Map
DEMOGRAPHY
User Locations
Edit Sentiments
MENTIONS
Training & Learning
Backtracking
Compare SNA
COMPARE
Compare Projects
Popularity vs
Favorability
Background Jobs
Upload Report
REPORTING
Download Report
User Management
ADMIN
Project Management
Client Management
Source Management
Label and Training
OPINION ANALYSIS
Opinion Chart
Insight Explorer

20. Data Lake
Keywords
KEYWORD + FILTER
20
Twits
twit
twit
twit
Filters

21. FREE TWITTER SEARCH AND STREAM API
21
History: 7 days
Start search
100% results

22. INSTAGRAM DATA CRAWLING
• Instagram: API + Selenium
22

23. RESULTS

24. TRENDS (18 SEPT – 16 NOV 2020)
24
our archived data
complete
data
Indonesia
Thai
Vietnam
Malay
7 days

25. TRENDS (7 DAYS): #1 THAI, #2 INDONESIA
25
Indonesia
Thai
Vietnam
Malay

26. VOLUME (7 DAYS): #1 THAI, #2 INDONESIA
26

27. SHARE OF VOICES (7 DAYS): TWITTER VS IG
27
Indonesia
Thai
Indonesia
Thai

28. USER PROFILE LOCATIONS
THAI (MORE INTERNATIONAL), INDONESIA (MORE LOCAL)
28
Indonesia
Thai

29. THAI FOOD
WIDE SPREAD (MORE INTERNATIONAL)
29

30. INDONESIAN FOOD
LESS DISTRIBUTED
30

31. SOCIAL NETWORK ANALYSIS: THAI FOOD
31

32. SOCIAL NETWORK ANALYSIS: INDONESIAN FOOD
32

33. THAI FOOD (IG): BEAUTIFUL PACKAGING
33

34. INDONESIAN FOOD (IG): LOCAL POSTINGS
34

35. HASHTAGS THAI FOOD (IG): INTERNATIONAL
35

36. HASHTAGS INDONESIAN FOOD (IG): MORE LOCAL
36

37. THAI FOOD (TWITTER): GOOD PACKAGING
37

38. INDONESIAN FOOD (TWITTER): LOCAL POSTINGS
38

39. HASHTAGS THAI FOOD (TWITTER): INTERNATIONAL
39

40. HASHTAGS INDONESIAN FOOD (TWITTER): MORE
LOCAL
40

41. TOP TWIT: THAI FOOD
41

42. TOP TWIT: THAI FOOD /2
42

43. TOP TWIT: INDONESIAN FOOD
43

44. TOP TWIT: INDONESIAN FOOD /2
44

45. TWITTER WORD CLOUDS: THAI FOOD
45

46. TWITTER WORD CLOUDS: INDONESIAN FOOD
46

47. PLUTCHIK’S WHEEL OF EMOTIONS
47
https://www.6seconds.org/2017/04/27/plu
tchiks-model-of-emotions/

48. LEXICON BASED ANALYSIS
• JOY
• senang, bahagia, suka, seneng, hepi, menyenangkan, happy,
menggembirakan, gembira, fun, sukacita, riang, ceria, …
• TRUST
• FEAR
• SURPRISE
• SADNESS
• DISGUST
• ANGER
• ANTICIPATION
48

49. EMOTION ANALYSIS: THAI FOOD
49
Love Thai food

50. EMOTION ANALYSIS: INDONESIAN FOOD
50
Many of promotions
Love Indonesian food

51. 51

52. 52

53. USER DEMOGRAPHY (TWITTER): THAI FOOD
53

54. USER DEMOGRAPHY (TWITTER): INDONESIAN FOOD
54

55. SUMMARY
• Twitter and Instagram can be used to capture conversation related to gastronomy,
and in this presentation related to foods, from Indonesia and its three neighboring
countries (Thailand, Malaysia, and Vietnam).
• Due to limited time, only the first two most popular countries are analyzed further
(Indonesia and Thailand).
• Using big data analytics and artificial intelligence, we can derive the following
insights from the conversations:
• which gastronomy is the most popular?
• how the gastronomy of each country are spread across social media users?
• how the users are connected in the conversation?
• what are the topics (hashtags) and type of foods that most popular?
• how are they looked like?
• what emotions are expressed by users?
• how the demography of users are distributed?
55

56. THANK YOU FOR LISTENING
56