USiCON UII Jogjakarta

1. CONTESTING LANGUAGE AND
RELIGIOUS DISCOURSE
IN VIRTUAL COMMUNITY IN
THE POST TRUTH ERA
Ismail Fahmi, Ph.D.
Director
PT. Media Kernels Indonesia
Ismail.fahmi@gmail.com
USiCON 2019
UIN SUNAN KALIJAGA, YOGYAKARTA
16 OCTOBER 2019

2. 2
1992 – 1997 S1, Teknik Elektro, ITB
2003 – 2004 S2, Information Science, Universitas Groningen, Belanda
2004 – 2009 S3, Information Science, Universitas Groningen, Belanda
2000 – 2003 Inisiator IndonesiaDLN (Digital Library Network pertama di Indonesia)
Mengembangkan Ganesha Digital Library (GDL)
Mendirikan Knowledge Management Research Group (KMRG) ITB
Membangun Digital Library ITB
2009 – Sekarang Engineer di Weborama, Perusahaan berbasis big data (Paris/Amsterdam)
2014 – Sekarang Founder PT. Media Kernels Indonesia, a Drone Emprit Company
2015 – Sekarang Konsultan Perpustakaan Nasional, Inisiator Indonesia OneSearch
2017 – Sekarang Dosen Tetap Magister Teknik Informatika Universitas Islam Indonesia
Ismail Fahmi, Ph.D.
Ismail.fahmi@gmail.com
Lahir: Bojonegoro, 1974
Founder Media Kernels Indonesia

3. QUESTIONS
• How the language and religious discourses are contesting in
virtual community in Indonesia?
• Topics of the case studies:
• Khilafah
• Kafir, Kuffar
• Hijrah
3

4. POST-TRUTH, WORD OF THE YEAR
4

5. TRUTH V.S. POST TRUTH
5

6. THE SITUATION
6
Our conversation and
attention are being
shaped online.

7. LARGER PROBLEM THAN FAKE NEWS
7
Bias, propaganda, and deliberately
misleading information are much
MORE PREVALENT than fake news.
Gilad Lotan
Head of Data Science @buzzfeed

8. MUCH MORE PREVALENT
8

9. THE QUESTION
9
How do we defend
the informed public?

10. INDONESIA IN DIGITAL

11. BIG DATA – BIG GROWTH
11

12. 12

13. 13

14. 14

15. 15

16. 16
MILLENIALSGEN Z

17. BIG DATA SYSTEM
17
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
DataIngest
Management&Queue
RealtimeJob
Processing
Instagram Crawler
Database Framework
ScheduledJob
Processing
Map Reduce
Sentiment
Analysis
Other
Processings
Data&Workflow
Management
Access
Visualization
YouTube Crawler
Analytics UI

18. CASE STUDY #1: KHILAFAH

19. TREND OF ‘KHILAFAH’ (3 MONTHS)
19

20. DATA SET OF ‘KHILAFAH’
20

21. SOCIAL NETWORK OF ‘KHILAFAH’ (TWITTER)
21
PRO KHILAFAH
PRO OPPOSITION
PRO GOVERNMENT

22. TOPIC NETWORK OF ‘KHILAFAH’ (TWITTER)
22
PRO KHILAFAH
PRO OPPOSITION
PRO GOVERNMENT
KASHMIR

23. EX-HTI NETWORK OF ‘KHILAFAH’ (TWITTER)
23
PRO KHILAFAH

24. HASHTAGS FOR ‘KHILAFAH’ (TWITTER)
24

25. HASHTAGS FOR ‘KHILAFAH’ (FACEBOOK)
25

26. HASHTAGS FOR ‘KHILAFAH’ (INSTAGRAM)
26

27. MEMES OF ‘KHILAFAH’ (TWITTER)
27

28. VIDEOS OF ‘KHILAFAH’ (TWITTER)
28

29. TOP TWITS OF ‘KHILAFAH’ (TWITTER) #1
29

30. TOP TWITS OF ‘KHILAFAH’ (TWITTER) #2
30

31. SUMMARY FOR ‘KHILAFAH’
• Polarization on the language ‘khilafah’ is clearly shown in the
virtual community conversation.
• The term ‘khilafah’ is heavily used by at least 3 clusters.
• Pro Khilafah: “We are the world Khilafah”
• Pro Gov: “Islam Yes, Khilafah No”; “Opposition is supporting Khilafah”
• Pro Opposition: “Pro gov are politicing ‘khilafah’ to achieve their goals”
• ‘Khilafah’ is not only a religious discourse, but now is heavily on
political agenda.
31

32. CASE STUDY #2: KAFIR, KUFFAR

33. TRENDS OF ‘KAFIR’ (3 MONTHS)
33

34. DATA SET OF ‘KAFIR’
34

35. SOCIAL NETWORK OF ‘KAFIR’ (GLOBAL)
35
PRO OPPOSITION
PRO GOVERNMENT
INTERNATIONAL

36. SOCIAL NETWORK OF ‘KAFIR’ (INDONESIA)
36
PRO OPPOSITION PRO GOVERNMENT

37. HASHTAGS FOR ‘KAFIR’ (TWITTER)
37

38. HASHTAGS FOR ‘KAFIR’ (INSTAGRAM)
38

39. TOP TWITS OF ‘KAFIR’ (TWITTER) #1
39

40. TOP TWITS OF ‘KAFIR’ (TWITTER) #2
40

41. SUMMARY FOR ‘KAFIR’
• The use of the term ‘kafir’ is also heavily polarized.
• The intention of the conversation depends on the cluster or
chamber where netizen belongs to.
41

42. CASE STUDY #3: HIJRAH
#alasantri, #pemudahijrah, #indonesiatanpapacaran, #pemudakristen, #anakmudakristen
v.s. #hijrah

43. TRENDS OF ‘PEMUDA HIJRAH’ (3 MONTHS)
43

44. DATA SET FOR ‘PEMUDA HIJRAH’
44

45. SOCIAL NETWORK OF ‘PEMUDA HIJRAH’
45

46. SOCIAL NETWORK OF ‘HIJRAH’
46
PRO OPPOSITION
PRO GOVERNMENT

47. CONTESTING LANGUAGE ON ‘HIJRAH’
47
PRO OPPOSITION
PRO GOVERNMENT

48. HASHTAGS FOR ‘PEMUDA HIJRAH’ (TWITTER)
48

49. HASHTAGS FOR ‘PEMUDA HIJRAH’ (INSTAGRAM)
49

50. MEMES OF ‘PEMUDA HIJRAH’ (TWITTER)
50

51. MEMES OF ‘PEMUDA HIJRAH’ (INSTAGRAM)
51

52. TOP TWITS OF ‘HIJRAH’ (TWITTER) #1
52

53. TOP TWITS OF ‘HIJRAH’ (TWITTER) #2
53

54. SUMMARY FOR ‘HIJRAH’
• The term ‘hijrah’ is getting very popular in Indonesia, not only
virtually but also offline.
• In the religious cluster, the term is accompanied with other words
to express the goals of the hijrah.
• Some goals of the ‘hijrah’ are too strick or narrow. This has
invited netizen from other clusters to explain the true meaning of
‘hijrah’ according to their references.
54

55. WHAT CAN WE DO?

56. @UB_Official
56

57. @itbofficial
57

58. @univ_indonesia
58

59. @Stanford
59

60. @mit
60

61. @harvard
61

62. SUMMARY

63. CONCLUSION
• In this presentation I show the use of big data technology to
collect, analyze, and visualize the conversation in the virtual
community on some contesting languages and religious
discourses.
• Clusters of netizen are contesting on the use and meaning of the
terms in the experiments.
• Further works and collaboration between scholars on religious
discourse and data scientists are strongly recommended to
reveal more findings and understanding.

64. TERIMAKASIH
Ismail Fahmi, PhD.
Ismail.fahmi@gmail.com
081289083894