Blogs

Social Media Sentiment and the Stock Market

This is not an assertion or a hypothesis. There have been research studies around the world, including a recent one by Indiana University Bloomington using Twitter data to predict the stock market. Behavioural finance researchers can now apply computational methods to large-scale social media data to better understand and predict markets.

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Are We Trapped in Our Own Social Media Bubbles?

In 2013, I spoke about the theory of “social media bubbles”. This concept was unheard of three to five years ago. However, the internet and social media such as Google, Facebook and Twitter have evolved and are now powered by sophisticated machine learning algorithms that work endlessly to predict user behaviour based on a set of online activities, mouse clicks and keywords. Some of the common machine learning algorithms used are Market-Basket Analysis, Naive Bayes Classifier and many other derivatives.

Read More »

Data-Driven Campaign Is The Future

In the last decade or so, most of the decisions by communication strategists, agencies and PR practitioners are based on “folk theories”. It means theories that have been developed, tested and refined over time by practitioners about what works and what doesn’t, without much empirical evidence to validate the effectiveness of the campaign outcome and the rationale behind the campaign design.

Read More »

2016 Sarawak Election Results: Social Media Impact to Voters

Sarawak Election 2016 gave the opportunity for 1.1 million Malaysian voters to choose their favourite political party. With a population of around 2.63 million people, the voters are sporadically spread through mountainous land area of 126,000 square kilometres. This makes Sarawak land size marginally larger than Ohio in the United States, which has 11.46 million people.

Read More »

Social Media Sentiment and the Stock Market

This is not an assertion or a hypothesis. There have been research studies around the world, including a recent one by Indiana University Bloomington using Twitter data to predict the stock market. Behavioural finance researchers can now apply computational methods to large-scale social media data to better understand and predict markets.

Read More »

Are We Trapped in Our Own Social Media Bubbles?

In 2013, I spoke about the theory of “social media bubbles”. This concept was unheard of three to five years ago. However, the internet and social media such as Google, Facebook and Twitter have evolved and are now powered by sophisticated machine learning algorithms that work endlessly to predict user behaviour based on a set of online activities, mouse clicks and keywords. Some of the common machine learning algorithms used are Market-Basket Analysis, Naive Bayes Classifier and many other derivatives.

Read More »

Data-Driven Campaign Is The Future

In the last decade or so, most of the decisions by communication strategists, agencies and PR practitioners are based on “folk theories”. It means theories that have been developed, tested and refined over time by practitioners about what works and what doesn’t, without much empirical evidence to validate the effectiveness of the campaign outcome and the rationale behind the campaign design.

Read More »

2016 Sarawak Election Results: Social Media Impact to Voters

Sarawak Election 2016 gave the opportunity for 1.1 million Malaysian voters to choose their favourite political party. With a population of around 2.63 million people, the voters are sporadically spread through mountainous land area of 126,000 square kilometres. This makes Sarawak land size marginally larger than Ohio in the United States, which has 11.46 million people.

Read More »