Winning Odds for Pakatan Harapan in Johor (GE14)

1. Introduction

On January 20^th 2018 a detailed listing of the 56 state seats being contested by Pakatan Harapan (PH) component parties in Johor was published by Malaysiakini (https://www.malaysiakini.com/news/409412). Based on this listing, the seat division is as follows:

• 18 seats contested by PPBM
• 12 seats contested by PKR
• 14 seats contested by DAP
• 12 seats contested by AMANAH

This report provides an overview of the seats contested by component parties in PH and the winning odds for each seat. Detailed election forecast results are not available at the moment due to the cost involved in running simulations, however the winning odds will give a rough idea of the swing in support that PH needs to win control of the state.

Analysis was performed based on the 2017 1^st Quarter (Q1) electoral roll, State and Federal seat results from the 13^th General Election (GE13) and individual historical voting patterns from GE12 (2008) and GE13 (2013).

A PDF copy of this report can be downloaded at https://drive.google.com/file/d/1zYr2-a3KlYJ_msfEqaeze4FrKrqWOeSC/view?usp=sharing

How Political Interest is Divided by Language on Facebook in Malaysia (July 2017)

1. Introduction

This document provides a measurement of the political party interests of Facebook users in Malaysia. This is based on public information collected from Facebook.

Some important notes to remember when interpreting Facebook figures:

1. Total population refers to Facebook users aged 13 years and above.
2. Potential voters refer to Facebook users aged 21 years and above.
3. Youth refers to Facebook users aged 13 – 20 years.
4. Gender breakdown figures do not always add up to the total. This may be due to Facebook users not sharing their gender, and also due to rounding errors in statistics provided by Facebook. State breakdown figures also do not add up to the total due to the same rounding errors.
5. Detailed statistics on Putrajaya are not available due to the small number of users in the territory.
6. Figures provided by Facebook are estimates. Some inaccuracies are to be expected, e.g. the sum of state totals not being equal to the national total.
7. Facebook users residing in Malaysia are not necessarily Malaysian citizens.
8. Interest in a topic is equal to the number of users expressing interest in a topic.
   1. To measure interest we used a combination of Facebook Interests (a collection of interests, activities, groups, pages, status updates and job history identified by a common term determined by Facebook e.g. ‘United Malays National Organization’) and specific Group and Page names (e.g. Friends of BN).
   2. These are used to collect the number of users interested in a given party/coalition/politician/group. For example, a user mentioning a party name in a status update; sharing a news link related to the party or sharing content from a party-affiliated page would count towards the total interest in that party
   3. Interest in a political party does not indicate support for the party, only awareness
   4. It is currently assumed that interest in PAS includes some interest in AMANAH as PAS leaders and members migrated to AMANAH
9. Audience refers to the population of users that express interest in a topic. Unless indicated, the audiences used in this report are composed of potential voters (users in Malaysia aged 21 years and above).
10. Based on our research to date, Pages that are of type ‘politician’ are not always included under related Facebook Topics. For example, not all ‘Tony Pua’ (MP, PJ Utara, DAP) Page likes are included under interest in ‘DAP’. However, because Facebook does not make Topic details available we cannot easily determine which politicians, if any, were included.
11. Statistics on the Opposition primarily refer to component parties of the former Pakatan Rakyat – PKR, PAS and DAP. This includes the ‘Pakatan’ brand name.
12. July 2017 statistics were collected during a 2-week period in July 2017. As such there may be some differences in totals for political parties when comparing different sections due to changes in collected statistics.
13. Statistics on the 2017 1^st Quarter electoral roll are estimates based on published changes to the 2016 gazetted roll. Ethnic breakdown for new voters are based on profiling methods that we developed and should be considered estimates.

2. List of Acronyms

The following table shows a list of acronyms used in this document.

Acronym	Full name
PR	Pakatan Rakyat
PH	Pakatan Harapan
BN	Barisan Nasional
UMNO	United Malays National Organisation
GERAKAN	Parti Gerakan Rakyat Malaysia (also known as PGRM)
MCA	Malaysian Chinese Association
MIC	Malaysian Indian Congress
PBB	Parti Pesaka Bumiputra Bersatu Sarawak
PKR	Parti Keadilan Rakyat
DAP	Democratic Action Party
AMANAH	Parti Amanah Negara
PAS	Parti Islam Se-Malaysia
PPBM	Parti Pribumi Bersatu Malaysia

3. An Overview of Malaysia’s Facebook User Population (July 2017)

3.1 Division by Age and Gender

There are currently 24 million Facebook users in Malaysia. 54.17% are men and 45.83% are women.

From this total, 19 million users are aged 21 years and above. 52.63% are men and 47.37% are women. These are the potential voters on Facebook.

The chart below shows the population distribution by age group. The largest segment of the population is aged between 21 – 30 years.

The table below shows the distribution of Facebook users by state, sorted by the total population:

State	Total (13+ yrs)	Male (%)	Female (%)	% of Malaysia
Perlis	40,000	52.50	47.50	0.17
Labuan	170,000	52.35	46.47	0.71
Kelantan	290,000	51.72	44.83	1.21
Terengganu	370,000	51.35	48.65	1.54
Negeri Sembilan	380,000	55.26	47.37	1.58
Melaka	390,000	53.85	46.15	1.63
Pahang	500,000	54.00	48.00	2.08
Kedah	610,000	54.10	47.54	2.54
Perak	880,000	51.14	48.86	3.67
Penang	990,000	51.52	48.48	4.13
Sabah	1,000,000	53.00	47.00	4.17
Sarawak	1,100,000	51.82	45.45	4.58
Johor	1,900,000	57.89	45.79	7.92
KL + Selangor	15,000,000	56.67	42.67	62.50

 

The table below shows the distribution of Facebook users by state aged 21 years and above.

State	Total (>=21 yrs)	Male (%)	Female (%)	% of Msia (>=21 yrs)	% of State (>=21 yrs)
Perlis	33,000	51.52	48.48	0.17	82.50
Labuan	140,000	52.14	45.71	0.74	82.35
Kelantan	230,000	52.17	43.48	1.21	79.31
Terengganu	290,000	51.72	48.28	1.53	78.38
Negeri Sembilan	310,000	54.84	48.39	1.63	81.58
Melaka	320,000	53.13	46.88	1.68	82.05
Pahang	400,000	55.00	47.50	2.11	80.00
Kedah	490,000	53.06	46.94	2.58	80.33
Perak	710,000	50.70	47.89	3.74	80.68
Sabah	790,000	53.16	46.84	4.16	79.00
Penang	840,000	50.00	47.62	4.42	84.85
Sarawak	840,000	53.57	46.43	4.42	76.36
Johor	1,600,000	55.00	45.00	8.42	84.21
KL + Selangor	12,000,000	56.67	44.17	63.16	80.00

 

Based on the last column we can see that Sarawak, Terengganu, Kelantan and Sabah have the highest proportion of young users (below 21 years).

As of 2017 Quarter 1, an estimated 21.64% of registered voters reside in KL and Selangor. In the National Census 2010, 24.35% of Malaysia’s citizens and 24.11% of Malaysia’s total population reside in KL and Selangor.

However according to statistics from Facebook, 62.50% of Facebook users in Malaysia reside in KL and Selangor. This includes Malaysians and foreigners who live there. This is an increase from 50% in August 2016.

The heavy concentration of users in KL and Selangor means that trending content in Malaysia in terms of shares and likes might not reflect what the country is talking about. When it comes to the analysis of interest in local issues such as politics, it is therefore important to evaluate the interests of users in different states.

3.2 Division by Language

The chart below shows the number of potential voters by language used on Facebook, based on information they have shared with Facebook:

Hindi/Tamil = users who use Hindi or Tamil. Only 20 thousand users use both languages

If we added the totals together there would be 30 million users. Given that there are only 19 million Facebook users, there is an overlap between users from each group. Many users speak multiple languages.

93% of potential voters on Facebook use English, Malay or Chinese languages. Because of this high coverage, we were able to design a set of formulas to break up these users into smaller, identifiable groups based on different combinations of spoken languages. The population of users in these groups can then be estimated. The results of this analysis are in the table below:

Language Group	Code	% of Population (>=21 years)	Description
Bilingual Malay + English	BME	40.26	Users who speak Malay and English. May also speak other languages except Chinese.
English Only / English + Other languages	EO	19.21	Users who speak English but do not speak Malay or Chinese. May also speak other languages.
Malay Only / Malay + Other languages	MO	13.95	Users who speak Malay but do not speak English or Chinese. May also speak other languages.
Bilingual Chinese + English	BCE	12.37	Users who speak both Chinese and English. May also speak other languages except Malay.
Other Languages Only	OTH	7.11	Users who do not speak English, Malay or Chinese
Chinese Only / Chinese + Other languages	CO	3.42	Users who speak Chinese but do not speak English or Malay. May also speak other languages.
Bilingual Malay + Chinese	BMC	1.84	Users who speak both Malay and Chinese. May also speak other languages except English.
Trilingual Malay + English + Chinese	TRI	1.84	Users who speak English, Malay and Chinese. May also speak other languages.

 

The proportion of each group is summarised in the chart below.

From the chart we can observe that:

• The Bilingual Malay + English (BME) group is both the largest group of users and largest subset of Malay speakers in the country
• Most Malay speakers on Facebook understand English
• The Bilingual Chinese + English (BCE) group is the 4^th largest group of users and largest subset of Chinese speakers in the country
• Most Chinese speakers on Facebook understand English
• A minority of users (3.68%, 700 thousand) speak combinations of Malay and Chinese

The Impact of Redelineation On The Selangor State Elections

1. Introduction

On September 15^th 2016 the Election Commission of Malaysia (Suruhanjaya Pilihanraya Malaysia) published the proposed redelineation of electoral boundaries for State and Federal constituencies. Under this proposal:

• No new Federal constituencies would be created
• 13 new State constituencies would be created in Sabah
• No new State constituencies would be created in states other than Sabah
• 12 Federal constituencies would be renamed
• 36 State constituencies would be renamed

This report provides an overview of the impact of state constituency redelineation on the Selangor State elections. Analysis was performed based on the 2016 1^st Quarter (Q1) electoral roll (before and after redelineation), State and Federal seat results from the 13^th General Election (GE13) and individual historical voting patterns from GE12 (2008) and GE13 (2013).

Recent Trends in Political Party Interest on Facebook in Malaysia (Aug 2016)

1. Introduction

This document provides a measurement of the political party interests of Facebook users in Malaysia. This is based on public information collected from Facebook.

Some important notes to remember when interpreting Facebook figures:

1. Total population refers to Facebook users aged 13 years and above.
2. Potential voters refer to Facebook users aged 21 years and above.
3. Youth refers to Facebook users aged 13 – 20 years.
4. Gender breakdown figures do not add up to the total. This may be due to Facebook users not sharing their gender, and also due to rounding errors by Facebook when dealing with specific age groups. State breakdown figures also do not add up to the total, due to the same rounding errors.
5. Figures provided by Facebook are estimates. Some inaccuracies are to be expected.
6. Facebook users residing in Malaysia are not necessarily Malaysian citizens.
7. Interest in a topic is equal to the number of users expressing interest in a topic.
   1. To measure interest we used a combination of Facebook Interests (a collection of interests, activities, groups, pages, status updates and job history identified by a common term determined by Facebook e.g. ‘United Malays National Organization’) and specific Group and Page names (e.g. Friends of BN).
   2. These are used to collect the number of users interested in a given party/coalition/politician/group. For example, a user mentioning a party name in a status update; sharing a news link related to the party or sharing content from a party-affiliated page would count towards the total interest in that party
   3. Interest in a political party does not indicate support for the party, only awareness
   4. It is assumed that interest in PAS includes interest in AMANAH as PAS leaders migrated to AMANAH
8. Audience refers to the population of users that express interest in a topic.
9. Based on our research to date, Pages that are of type ‘politician’ are not always included under related Facebook Topics. For example, not all ‘Tony Pua’ (MP, PJ Utara, DAP) Page likes are included under interest in ‘DAP’. However because Facebook does not make Topic details available we cannot easily determine which politicians, if any, were included.
10. Statistics on the Opposition primarily refer to component parties of the former Pakatan Rakyat – PKR, PAS and DAP. Interest in PSM is included in total statistics for the Opposition, but is not listed separately due to its small audience.

 

2. Interest in Political Parties on Facebook

The following graph shows the partisanship of interest in political parties by Facebook users in Malaysia aged 21 years and above. Interest in PAS is assumed to include interest in AMANAH because Facebook has not made separate AMANAH figures available yet.

Out of 8.4 million users in Malaysia (aged 21 years and above) that are interested in BN or Opposition parties:

• 54% are male and 46% are female
• 3 million are interested in Opposition parties
• 8 million are interested in BN parties
• 76% (400 thousand) are exclusively interested in Opposition parties
• 52% (2.9 million) are interested in a mix of Opposition and BN parties
• 71% (5.1 million) are exclusively interested in BN parties

As of August 2016 the level of exclusive interest in 60.71% for BN and 4.76% for the Opposition. This is a record high for BN and a record low for the Opposition since we began tracking these statistics in December 2012.

Evaluating Voter Support in Kuala Kangsar and Sungai Besar Using General Election Results and Twitter

1. Background

Prior to the 13th General Election (GE13) we came up with a methodology of predicting election results based on voting patterns in previous elections.

Our method relied on mapping polling lane results to individual voters. This process assigned probability values (chance of turnout; chance of voting for each coalition) to the voter that was not affected if they migrated to another constituency. This is important because between GE12 and GE13 527,849 voters migrated to different constituencies.

The impact of voter migration cannot be measured for a single seat by comparing the results of GE12 and GE13 for that seat. An analysis of the whole country needs to be performed. New voter registrations, voters passing away and voters no longer eligible to vote are other factors that require deep analysis.

After GE13 we were able to apply the same estimation method to voters based on GE13 results. By comparing the shift in probabilities we are able to calculate the swing in support for each coalition. Because we base our calculations on individual voters, we are able to calculate shifts in support based on combinations of the following dimensions:

• By Age
• By Race
• By Gender
• By Urban Development Category (rural / semi-urban / urban)
• By Parliament/State Assembly Seat
• By Polling District
• By Locality
• By Seats Won by Specific Parties

Any voter whose level of support cannot be determined is assigned a probability of 50% and categorised as a fence-sitter. The most reliable metric is age because voters are separated into polling lanes based on age. Additionally we have also categorised the 222 Parliament constituencies as rural, semi-urban or urban based on satellite imagery. The descriptions of each category are:

Rural = villages (kampungs) / small towns / farmland distributed within the seat. Rural seats tend to be physically large with a low population.

Semi-urban = larger towns and/or numerous small towns, may include villages as well

Urban = cities where a majority of the seat is covered by some form of urban development

For this report we will focus on how Pakatan Rakyat (PR) and Barisan Nasional (BN) performed with regular voters (pengundi biasa) in P67.Kuala Kangsar and P93.Sungai Besar. This will give a sense of what to expect during the by-elections to be held on June 18^th 2016.

In addition to this we will also briefly examine political interest from Twitter users based in these constituencies. This may identify patterns that can be linked to urban youth in these areas.

Postal and early voters are not part of this analysis. They need to be analysed separately due to their different voting process and difficulties in campaigning to both groups.

Please remember that unless otherwise stated, all statistics in this analysis refer to regular voters only. We do not have access to the electoral roll being used for these by-elections and will be relying on estimated figures from the electoral roll for 2015 Q4 (4^th quarter).

2. Seat Demographics

Demographics for Sungai Besar and Kuala Kangsar are listed below.

Detail / Seat	P93. Sungai Besar	P67. Kuala Kangsar
State	Selangor	Perak
Voters (GE13)	42,923 (2.09% of Selangor voters)	33,607 (2.38% of Perak voters)
Urban Development Category	Rural	Semi-urban
Majority Race	Malay	Malay
Contesting Parties (GE13)	UMNO, PAS	UMNO, PAS, Independent
Winner (GE13)	UMNO	UMNO
Twitter Users	1,049 (0.66% of Selangor users) 89% primarily use Bahasa Malaysia	660 (2.39% of Perak users) 81% primarily use Bahasa Malaysia

 

The following charts show the estimated ethnic divide among voters in both seats based on our estimated electoral roll for 2015 Q4. This covers all voters (postal, early and regular).

Changes in Sungai Besar since GE13 (up to 2015 Q4):

• Malay voters increased by 0.33 percentage points
• Chinese voters decreased by 0.4 percentage points
• Indian voters increased by 0.06 percentage points
• 1,260 voters removed
• 1,394 new voters
• 171 voters migrated in from other constituencies

 

Changes in Kuala Kangsar since GE13 (up to 2015 Q4):

• Malay voters increased by 0.46 percentage points
• Chinese voters decreased by 0.45 percentage points
• Indian voters decreased by 0.015 percentage points
• 1,153 voters removed
• 1,079 new voters
• 185 voters migrated in from other constituencies

Both seats have had an increase in the percentage of Malay voters, and a decrease in the percentage of Chinese voters.

Facebook Census of Political Interest in Malaysia, August 2015

1. Introduction

This document provides a measurement of the political interests of Facebook users in Malaysia and a brief analysis of recent trends. This is based on public information collected from Facebook. Characteristics and interests were chosen based on what would be most relevant to political analysts.

Statistics cover users aged 21 years and older unless otherwise specified.

Some important notes to remember when interpreting figures:

1. Total population refers to Facebook users aged 13 years and above.
2. Potential voters refer to Facebook users aged 21 years and above.
3. Youth refers to Facebook users aged 13 – 20 years.
4. Gender breakdown figures do not add up to the total. This may be due to Facebook users not sharing their gender, and also due to rounding errors by Facebook when dealing with specific age groups.
5. Figures provided by Facebook are estimates. Some inaccuracies are to be expected.
6. Facebook users residing in Malaysia are not necessarily Malaysian citizens.
7. Interest in a topic is equal to the number of users expressing interest in a topic.
   1. To measure interest we used a combination of Facebook Topics (a collection of interests, activities, groups, pages, status updates and job history identified by a common term determined by Facebook e.g. ‘United Malays National Organization’) and specific Group and Page names (e.g. Friends of BN).
   2. These are used to collect the number of users interested in a given party/coalition/politician/group. For example, a user mentioning a party name in a status update; sharing a news link related to the party or sharing content from a party-affiliated page would count towards the total interest in that party
   3. Interest in a political party does not indicate support for the party, only awareness
8. Audience refers to the population of users that express interest in a topic.
9. Based on our research to date, Pages that are of type ‘politician’ are not always included under related Facebook Topics. For example, not all ‘Tony Pua’ (MP, PJ Utara, DAP) Page likes are included under interest in ‘DAP’. However because Facebook does not make Topic details available we cannot easily determine which politicians, if any, were included.
10. Statistics on the Opposition primarily refer to component parties of the former Pakatan Rakyat – PKR, PAS and DAP. Interest in PSM is included in total statistics for the Opposition, but is not listed separately due to its small audience.

Opinion Analysis of Twitter Users in Malaysia on Muhyiddin Yassin’s Dismissal

1. Background

On July 28th 2015 a new Cabinet line-up was announced by Malaysia’s Prime Minister Najib Razak.

Former Deputy Prime Minister Tan Sri Muhyiddin Yassin was absent from the new Cabinet. Zaid Hamidi replaced him for the post of Deputy Prime Minister and Mahdzir Khalid replaced him for the post of Minister of Education.

Muhyiddin being dropped from the Cabinet followed speculation that this would happen due to his remarks about 1MDB on Sunday, July 26th. He was reported to have asked for PM Najib to personally explain the 1MDB issue and answer the allegations by the Wall Street Journal (WSJ) [1].

2. Our Analysis

We performed opinion-based analysis on 502 users based in Malaysia who tweeted about Muhyiddin and related terms on July 28th 2015. The margin of error is +/- 4.37%.

Users were selected based on their tweet content and activity during this period. Sampling was done per-state based on the current estimated user population.

Spammers, news agencies and accounts with automated tweets were not included in the sample.

From this dataset we analysed the individual Twitter user timelines to determine their opinion. This took their tweets, retweets and conversations into account.

Our goal was to gauge public reaction by Twitter users in Malaysia to the removal of Tan Sri Muhyiddin Yassin to see if they supported the decision.

Users who were tweeting about related topics (PM Najib; the Cabinet line-up) but not in response to Muhyiddin Yassin’s dismissal were not included in the sample. However we took note of what these users were saying for section 4 (Additional Opinions).

Based on this analysis we categorised users as belonging to one of the following categories:

1. Positive
2. Neutral
3. Negative (support Muhyiddin)

These were further divided into the following categories based on which party they chose to support/criticise:

1. Positive
2. Neutral
3. Negative (support Muhyiddin)
4. Negative (support Muhyiddin, critical of Najib)
5. Negative (support Muhyiddin, he must oppose Najib)

The results are shown in the following charts.

Analysing Pakatan Rakyat’s Performance with Malay Voters in Peninsular Malaysia (GE13)

1. Background

Prior to the 13th General Election (GE13) we came up with a methodology of predicting election results based on voting patterns in previous elections (reference).

Our method relied on mapping polling lane results to individual voters. This process assigned probability values (chance of turnout; chance of voting for each coalition) to the voter that was not affected if they migrated to another constituency. This is important because between GE12 and GE13 527,849 voters migrated to different constituencies.

The impact of voter migration cannot be measured for a single seat just by comparing results of GE12 and GE13 for that seat. An analysis of the whole country needs to be performed. New voter registrations, voters passing away and voters no longer eligible to vote are other factors that require deep analysis.

After GE13 we were able to apply the same estimation method to voters based on GE13 results. By comparing the shift in probabilities we are able to calculate the swing in support for each coalition. Because we base our calculations on individual voters, we are able to calculate shifts in support based on combinations of the following dimensions:

• By Age
• By Race
• By Gender
• By Urban Development Category (rural / semi-urban / urban)
• By Parliament/State Assembly Seat
• By Polling District
• By Locality
• By Seats Won by Specific Parties

Any voter whose level of support cannot be determined is assigned a probability of 50% and categorised as a fence-sitter. The most reliable metric is age because voters are separated into polling lanes based on age. Additionally we have also categorised the 222 Parliament constituencies as rural, semi-urban or urban based on satellite imagery (reference). The descriptions of each category are:

Rural = villages (kampungs) / small towns / farmland distributed within the seat. Rural seats tend to be physically large with a low population.

Semi-urban = larger towns and/or numerous small towns, may include villages as well

Urban = cities where a majority of the seat is covered by some form of urban development

For this report we will focus on how Pakatan Rakyat (PR) and Barisan Nasional (BN) performed with regular Malay voters (pengundi biasa) in Peninsular Malaysia. 184 of the total 222 Parliament seats are in Peninsular Malaysia, where most of the Malay electorate is concentrated.

Elections are won based on the number of seats. However our analysis will mainly be on the Malay electorate treated as a set of voters ignoring constituency boundaries. We will examine this at the state-level and for Peninsular Malaysia. This will allow us to see patterns that are not obvious at the seat-level.

Postal and early voters are not part of this analysis. They need to be analysed separately due to their different voting process and difficulties in campaigning to both groups.

Please remember that unless otherwise stated, all statistics in this analysis refer to regular voters in Peninsular Malaysia only.

Opinion Analysis on Breakup of Pakatan Rakyat by Users in Malaysia

1. Background

On June 16th 2015 the Democratic Action Party (DAP) released a statement saying that Pakatan Rakyat (PR) ceases to exist following the Parti Islam Se-Malaysia (PAS) Muktamar’s motion to sever ties with DAP [1]. The DAP also pledged to work with PKR and any other parties to defeat Barisan Nasional (BN).

On June 17th 2015 Parti Keadilan Rakyat (PKR) released a statement saying that Pakatan Rakyat no longer functions formally [2]. PKR also stated that they would work to build a coalition to defeat BN.

In the days that followed there was confusion on whether Pakatan Rakyat as a coalition was truly dead. This is illustrated by the following public statements by component party leaders:

• June 18th: PAS Elections Director Datuk Mustafa Ali stated that PAS was not dead, only ‘fainted’ [3]
• June 19th: PAS President Hadi Awang declared that PR was not dead [4]
• June 20th: DAP Parliamentary leader Lim Kit Siang responded by saying PR was dead [5]
• June 20th: PKR Deputy Youth Chief insists that PR is not dead [6]

Currently the Opposition-held state governments of Kelantan, Selangor and Penang appear to be continuing as state-level coalition governments. Whether the coalitions will continue to use ‘Pakatan Rakyat’ to refer to themselves is unclear.

2. Our Analysis

We performed opinion-based analysis on 475 users based in Malaysia who tweeted about Pakatan Rakyat, its component parties and related terms from June 16th – June 20th 2015. The margin of error is +/- 4.5%.

Users were selected based on their tweet content and activity during this period. Sampling was done per-state based on the current estimated user population.

Spammers, news agencies and accounts with automated tweets were not included in the sample.
From this dataset we analysed the individual Twitter user timelines to determine their opinion. This took their tweets, retweets and conversations into account.

Our goal was to gauge public reaction by Twitter users in Malaysia to the breakup of Pakatan Rakyat.

Opinion Analysis on Support for Hudud in Selangor and Kelantan

On March 19th 2015, The Syariah Criminal Code Enactment (II)(1993) Amendment 2015 (commonly referred to as hudud) was unanimously passed by the Kelantan State Assembly.

We performed opinion-based analysis on 851 users based in Selangor and Kelantan who tweeted about Hudud from March 18th 2015 – March 22nd 2015.

396 users were from Kelantan (margin of error: 4.92%) and 455 users were from Selangor (margin of error: 4.59%).

Users were selected based on their tweet content and activity during this period. Sampling was done per-state based on the current estimated user population.

Spammers, news agencies and accounts with automated tweets were not included in the sample. Users talking solely about other issues (e.g. the BFM ‘kupas’ hudud video) were also excluded as we wanted to analyse users with opinions about hudud itself.

From this dataset we analysed the individual Twitter user timelines to determine their opinion about hudud. This took their tweets, retweets and conversations into account.

Our goal was to gauge public opinion by Malaysian users on their support for the law, in light of the enactment being passed in Kelantan.

Based on this analysis we categorised users as belonging to one of the following categories:

1. Not Support Hudud
2. Support Hudud
3. Uncategorised (No Opinion / Other Opinions)

Uncategorised opinions are from users who have no clear opinion that matched the criteria of the other stated categories.

Here are the results: