Observing Malaysian Social Media

Posts Tagged ‘Twitter

An Analysis of Opinions on Tun Mahathir, Trends in Political Interest on Facebook and Political Support by Malay Youth in Malaysia

1. Introduction

This report is divided into the following sections:

  1. Introduction
  2. List of Acronyms
  3. An Analysis of Opinions on Tun Mahathir Working With the Opposition Following the Citizens Declaration in March 2016
  4. An Analysis of Opinions on Tun Mahathir as the PM candidate for Pakatan Harapan by Malay Youth in Peninsular Malaysia
  5. Facebook Trends for Interest in Tun Mahathir and PM Najib
  6. Malaysia’s Twitter Demographics Overview
  7. Interest in Tun Mahathir on Twitter
  8. Twitter Sentiment Analysis for PM Najib and Tun Mahathir
  9. Conclusion

Each section will explore indicators from Twitter and Facebook to determine the level of support for Tun Mahathir, PM Najib and political parties.

This study was originally published on our Facebook Page on May 9th, 2018.

A PDF copy of this report can be downloaded from https://drive.google.com/open?id=13EIGTHlY8eClRslaUNhgg30j9ywAW9Fj

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Written by politweet

May 15, 2018 at 3:34 am

The Most Followed Twitter Users in Malaysia (Oct 2017)

Since 2014 we have been building up a database of profiled Twitter users in Malaysia. We currently have over 630,000 profiled user accounts that are location-based. What this means is that we can analyse opinions and interests not just by state, but by area (e.g. cities, constituencies, campuses, malls, suburbs / taman). We have demonstrated the application of this database for opinion analysis (browse here) and by-elections (link). We are currently working on improving the level of detail for our profiles and are now sharing part of our research results with the public.

Using a sample of 24,677 users from our database, we collected their lists of Twitter ‘friends’ (user accounts that people follow). This resulted in a list of 2.07 million users. This list was then used to summarise the top 207,500 most-followed users by users in Malaysia.

The Top 10 most-followed Twitter users are below:

Rank @ScreenName Name Market Reach (%)
1 instagram Instagram 39.385
2 Khairykj Khairy Jamaluddin 35.665
3 9GAG 9GAG 32.577
4 Matluthfi90 Matluthfi90 27.459
5 yunamusic Yuna Zarai 25.064
6 501Awani Astro AWANI 23.982
7 NajibRazak Mohd Najib Tun Razak 23.625
8 waktuSolatKL Waktu Solat WP KL 22.653
9 SantapanMinda Santapan Minda 22.134
10 ustazharidrus Ust Azhar Idrus 21.818

Market reach is defined as the percentage of users in Malaysia who follow that Twitter user. Based on this list, Khairy Jamaluddin (MP for Rembau, Minister of Youth and Sports, UMNO Youth Leader) is both the most-followed person and most-followed Malaysian in the country. But his market reach is only 35.665% of users in Malaysia. This shows that no single user on Twitter ‘owns’ the Malaysian market. Because we are using profiled users, the possibility of fake followers (or phantoms, fake accounts etc.) is a non-issue.

The Top 10 users have a combined market reach of 82.25%. Most Twitter users in Malaysia have a market reach that would be considered small. But a small market reach does not mean that a tweet has no chance of going viral. Due to the high degree of connectivity between Twitter users plus the Twitter Search factor, there is always a chance for a tweet getting retweeted and spread throughout the network.

Using the data that we collected, we performed a network analysis on how the most-followed Twitter users are connected to each other based on their followers. For this analysis we used the top 4,704 users. This covers all user accounts followed by users in Malaysia with a minimum market reach of 0.61%.

Users that have a shared appeal (affinity) will have overlapping audiences, which is equal to strong connections if the overlap is high. For example, users that tweet primarily about football will draw interest from other people who like football.

Based on the network analysis we generated a map showing clusters of users with a strong affinity for each other. Based on where they are in the map, you can see the affinity that different popular users have with each other. Users with a greater market reach are shown in a larger font, coloured from a scale ranging from blue (least popular) to orange to red (most popular).


The full-size version can be viewed at our Flickr page here.

At a glance you can see that the top users are close to each other where @Khairykj and @instagram are visible. As stated earlier the Top 10 users have a combined market reach of 82.25%. Despite the fact that these users don’t tweet about the same topics, their proximity to each other is due to their mass market appeal.


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Analysis of Opinions on Lim Guan Eng’s Corruption Charges by Twitter Users in Malaysia

1. Background

On March 17th 2016, Shabudin Yahaya (BN MP for Tasek Gelugor) alleged that the Chief Minister of Penang, Lim Guan Eng was involved in the sale of two plots of land in Taman Manggis, Penang to a company whose owner was connected to the owner of a bungalow purchased by Lim Guan Eng. The purchase of the bungalow was alleged to have been below the market-price [1].

Comparisons were made between these allegations and former Menteri Besar of Selangor, Khir Toyo’s case where he was convicted for abusing his power to acquire land and property below the market-price.

Following these allegations, a series of exposes and more allegations surfaced online. MACC conducted investigations and on June 29th Lim Guan Eng was arrested and held overnight.  On June 30th he was charged with corruption in the Penang High Court. His former land-lady, Phang Li Koon was also charged for her involvement.

The charges faced by Lim Guan Eng are described below:

“Lim is facing two charges for corruption – one under Section 165 of the Penal Code and another Section 23 of the Malaysian Anti-Corruption Act (MACC) 2009 — over his approval of an application from Magnificent Emblem to convert a piece of land from agricultural to residential use, as well as over his purchase of a house from the firm’s director, Phang, for RM2.8 million, which was below the property’s market value of RM4.27 million.” [2]

Since the story broke in March we tracked mentions of Lim Guan Eng, Taman Manggis, Khir Toyo and other related terms to gauge the response to the initial story and on-going exposes.

2. Initial Analysis (March 17th – April 30th)

We initially examined tweets by 10,627 users from March 17th – April 30th 2016 mentioning the keywords related to allegations against Lim Guan Eng.

What we found was the topic was popular mainly with users with a strong partisan interest in Malaysian politics. This issue did not draw enough interest from the general public – it was not worth talking about, and those who did tended to express disinterest or only retweet news articles.

The topic also drew more interest from users based in Kuala Lumpur, Selangor and Penang. 59% of users tweeting about the topic (not including retweets) were based in these 3 states. The highest drop in interest was from users in Johor, which made up 8.63% of the local population (1.96 points lower than the proportional average).

There was also a high degree of spammed tweets, with spammed tweets outnumbering non-spammed tweets on some days. This can be seen in the chart below:


1,358 users spammed 49,223 tweets. In other words, 12.8% of the users spammed 41.8% of the total tweets.

From a manual reading of non-spammed tweets during this period, we found that tweeted opinions about the scandal fell mainly into the following categories:

  • Users not interested in Lim Guan Eng’s scandal
  • Users complaining about excessive media coverage. Most complaints implied users were bored or not interested in listening to the repeated allegations.
  • Users wanting Lim Guan Eng to be investigated
  • Users comparing Lim Guan Eng’s case with Khir Toyo’s case
  • Users criticising Lim Guan Eng’s responses to the allegations
  • Users critical of BN and DAP, equating both to be corrupt
  • Users defending Lim Guan Eng. Among the more popular reasons were:
    • BN / UMNO / PM Najib are considered to be worse
    • The discount isn’t that big / there is nothing wrong with a good deal
    • The 1MDB scandal is much bigger and more important than Lim Guan Eng’s scandal
    • Khir Toyo’s house is bigger

Users defending Lim Guan Eng were a small minority. There was little evidence of pro-DAP or pro-Opposition users being mobilised to defend Lim Guan Eng.

Out of 44 DAP politicians actively tweeting in this period, only 27 politicians tweeted/retweeted tweets mentioning Lim Guan Eng or keywords related to the allegations. This does not include images or tweets not mentioning related keywords. By not talking about the allegations the 17 politicians missed an opportunity to contribute to Lim Guan Eng’s defence on Twitter.

Because of the low level of interest from the general public and the high degree of spam, we could not do a detailed opinion analysis at the time.

3. Analysis of Opinions on Lim Guan Eng’s Corruption Charges (June 29th – July 6th)

We examined tweets by 8,365 users from June 29th – July 6th 2016 mentioning keywords related to allegations against Lim Guan Eng. The daily interest is shown in the graph below.


We then performed opinion-based analysis on 520 users based in Kuala Lumpur, Selangor and Penang. The margin of error is +/- 4.3%.

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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 18th 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 (4th quarter).

2. Seat Demographics

Demographics for Sungai Besar and Kuala Kangsar are listed below.

Detail / Seat P93. Sungai Besar P67. Kuala Kangsar






Voters (GE13)




(2.09% of Selangor voters)




(2.38% of Perak voters)


Urban Development Category






Majority Race






Contesting Parties (GE13)




UMNO, PAS, Independent


Winner (GE13)







Twitter Users





(0.66% of Selangor users)

89% primarily use Bahasa Malaysia



(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.

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Written by politweet

June 11, 2016 at 9:25 am

Popular Chinese New Year Content Shared By Users in Malaysia (2016)


The first day of Chinese New Year was celebrated worldwide on February 8th 2016. We collected tweets mentioning Chinese New Year in English and Bahasa Malaysia from February 7th – February 12th 2016. This was limited to the most common phrases – ‘Tahun Baru Cina’, ‘Chinese New Year’, ‘Gong Xi Fa Cai’, ‘CNY’ and similar spellings. Our focus was on identifying the content that was widely shared and the demographics of users tweeting Chinese New Year greetings.

From the tweets collected we prepared listing of popular tweets and media shared by users in Malaysia, limited by the language used. More details on the methodology used are at the end of this post.

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Written by politweet

February 25, 2016 at 12:36 pm

How Twitter Users Reacted to News of Lee Kuan Yew’s Passing

Singapore’s founding father and first Prime Minister, Mr.Lee Kuan Yew passed away at 3.18 AM on March 23rd 2015. What follows are statistics and a selection of popular tweets about Lee Kuan Yew shared by users online in response to the news. Tweets from news agencies have been filtered out of the list. For a list of business services that we provide please visit our main site.
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Written by politweet

March 24, 2015 at 4:38 am

The Most Shared Images in Malaysia on Twitter, Feb 2015

Each day we collect hundreds of thousands of tweets from Twitter users in Malaysia. Based on this sample, we have ranked the most-shared images for the month of February. The list is presented below, sorted by the number of retweets worldwide. For a list of business services that we provide please visit our main site.

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Written by politweet

March 14, 2015 at 1:00 am

Posted in Social Media

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Sentiment Analysis on Selangor Menteri Besar Crisis


We performed opinion-based sentiment analysis on 2,062 users who tweeted about the Selangor Menteri Besar crisis from August 9th – August 15th 2014. These users were randomly selected based on tweets we collected since the crisis began. Spammers, news agencies and accounts with automated tweets were not included in the sample.

Our goal initially was to gauge public opinion primarily on whether to keep or remove Tan Sri Khalid Ibrahim. However mixed opinions emerged that allowed us to gauge responses to other parties involved e.g. Pakatan Rakyat (PR), Wan Azizah and Anwar Ibrahim. We were also able to gauge support for the State Assembly to be dissolved and state elections called.

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Top 20 Shared Photos Following Anwar Ibrahim’s Verdict

At 5pm today, Federal Opposition Leader Anwar Ibrahim was found guilty of sodomy by the Court of Appeal and subsequently sentenced to five years jail. Judge Datuk Balia Yusof Wahi allowed a stay on sentencing pending an appeal, and granted bail of RM10,000.

The following is a list of the most shared photos on Twitter mentioning Anwar Ibrahim and @anwaribrahim from 4pm – 8.30pm, March 7th 2014. Ranking is done by the number of users sharing the URL of the photo, not the number of retweets received.
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Written by politweet

March 7, 2014 at 8:59 pm

Popular Tweets from #Kangkung

#Kangkung was a Malaysian social media meme that started yesterday on January 13th 2014. It was prompted by a brief video clip of Prime Minister Najib Razak giving a speech as seen below (from minute 0:46 onwards):

In the video, the PM spoke about the price fluctuation of goods and questioned why the government gets criticised when prices increase but doesn’t get praised when prices decrease. He then gave the example of kangkung (water spinach) that had recently dropped in price. Netizens responded with all kinds of mocking statements and images deriding the PM for this statement, primarily using the hashtag #Kangkung.
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Written by politweet

January 14, 2014 at 3:31 am