The Science of Engagement: Analyzing Viewer Behavior in Singaporean Live Streams

In conjunction with an increasing global trend of new media development, the consumption of live streaming in Singapore has become a widespread practice. Key drivers such as improved internet speeds, the proliferation of smartphones, and an increasing internet penetration rate have significantly lowered the barriers to access the internet and led to an increasing level of consumer engagement in online activities. According to the We Are Social report, the average Singaporean spends 12 hours and 57 minutes a day engaging in various types of media. A significant portion of this media consumption involves platforms such as YouTube and Twitch, where users create and consume live streaming Singapore content online. Live streaming Singapore as a concept itself has evolved in recent years from being a casual hobby to a high-potential means of revenue for content creators. Platforms such as Twitch have created new monetization methods, primarily through subscriptions and donations, incentivizing users to create entertaining content. Combined with the rise of eSports, live streaming has also become a job for semi-pro and professional gamers. These trends have created an environment where content creators are highly motivated to increase channel traffic and provide high-quality entertainment to their viewers. In the case of Singapore, the live streaming landscape is highly diverse with content creators of various nationalities and streaming styles. Due to the Singaporean multi-racial policy, it is also common to find content creators using their native languages to reach out to viewers of similar ethnic backgrounds. With so much diversity and competition among creators, it has become essential to understand the preferences and viewing behavior of viewers.

Overview of Live Streaming in Singapore

In recent years, live streaming has gained global popularity and is regarded as an emerging medium for future content delivery, with millions of users broadcasting and viewing content at any given time. The development of live streaming platforms such as Twitch, YouTube, and Azubu has made live streaming more accessible for viewers and broadcasters, thus it is no surprise to see Singaporeans partaking in live streaming. Although Twitch has opened its Singapore servers in 2013 to provide better infrastructure for local streamers, the global platform has attracted an international audience base. However, most broadcasting still takes place on international platforms, and availability of local servers has not hindered the growth of global streaming sites. There has also been an increasing trend in the use of live streaming on social media platforms, particularly on Facebook and Instagram, to engage viewers for commercial and personal use. With the variety of content and platforms, live streaming has become an integrated part of online activity for many Singaporeans.

Importance of Analyzing Viewer Behavior

And Singapore, like many other countries, has a significant amount of video gamers and viewers tuning into video game content. These can consist of locally born Singaporeans or expatriates of other nationalities. Live stream video gaming is also a growing trend in Singapore. Considering the global nature of live stream video gaming, many of these Singaporeans may be watching live streams of video games hosted by people from around the world. These reasons make Singapore an excellent representative sample for global trends in live stream video gaming. By observing viewer behavior in Singaporean live streams, it can offer an accurate glimpse of the global viewer population.

This research is a preliminary attempt to understand viewing patterns on live stream video gaming in a global city-state, now Singapore is a country that is an excellent representative sample for global trends. Its demographic diversity consists of people from around the world, and global media trends are quickly adopted within the country itself. Video gaming is a recreational activity conducted by people of all ages, whether it is playing video games themselves or watching videos of others play video games.

Streaming content providers, such as Netflix, Hulu, and Amazon Instant Video, have already demonstrated that online streaming will eventually replace traditional television. And in a society where online streaming is integrated with daily life, it is important to understand the new trends of online video viewers. Live streaming is one of these new trends. While it is a concept that has been around since the early 2010s, it has gained little focus in media psychology research. In recent years, live streaming has begun to be a widely available service on a global scale, so understanding viewer behavior on live streams will be beneficial to both viewers and live stream broadcasters/content providers.

Analyzing viewer behavior has always been a popular research topic in communication studies. It is critical to understand the patterns of television program audiences to improve the overall viewing experience, which can benefit both viewers and media producers. This is also the case with online video streaming. As online technology advances, more people around the world are streaming videos over the internet, and it is becoming a global phenomenon.

Objectives of the Study

A study done by Razmig Hovaghimian, CEO of Viki streaming services, has also professed that Southeast Asia is an emerging market for on-demand TV shows. With this in mind, it would be highly beneficial to understand viewer behavior on this type of media in order to better predict how Singaporeans might interact with media of similar nature in the near future.

Live streaming media and on-demand TV shows are already prevalent in countries such as the United States, with websites like and Netflix. Anecdotal evidence suggests that viewers in Singapore are already partaking in such media via proxy servers to fake IP addresses in order to access region blocked content.

As Singapore moves toward its goal of being a Smart Nation, it is inevitable that the internet will be integrated into various domains of everyday life to enhance communications and make information more readily available. This would include the integration of internet media into the local television landscape.

The main objective of the study is to understand viewer behavior in Singapore when receiving and interacting with live streaming media. The media being examined will be in the form of a web broadcast, in which the subjects are limited only to streamed online TV shows, and the online transmissions of previously aired TV shows.

Viewer Engagement Metrics

High variance in viewer count over the event time can indicate a lack of punctuality in the viewers or uncertainty in event quality at that time. This information is invaluable for insights on improvements for the next event.

During the measurement of these metrics, it is important to note the time periods of promotion for the event and the event type. Different games or community events may attract a different target audience, and hence bonus viewership from promotions may not accurately express the success of the event.

Average duration of view implies the retention rate of the audience. A higher duration indicates that viewers are more interested and likely to attend similar events in the future.

Total chat messages showcase the activeness and interactivity of the audience. Higher levels of chat, on average, imply that the viewers are more engaged, and feedback from the audience can be very important in improving the quality of the event.

Total viewer count is the most intuitive metric for gauging popularity. For professional streams, more viewers make the event more attractive and worthwhile.

To evaluate the popularity and importance of live streaming, we first examine the viewer engagement metrics, including the total viewer count, total chat messages, and average duration of view. These are the main quantifiers that can show the success of a live streaming event.

Factors Influencing Viewer Engagement

The overall average viewer-high engagement is 36%, with a low of 18% and a high of 73.8%. Three streams (A, B and E) had greater than 50% subscriber viewership. It was found that there is a small positive correlation between engagement and duration of study. The more hours, the higher the engagement. However, this does not take into account concurrent viewership, which is a more accurate gauge of a stream’s success. A medium negative correlation was seen between engagement and time of streaming. This indicates that scheduling streams during certain times or days can greatly affect the expected engagement, with time and day being a leading factor of engagement in all of these streams. A small negative correlation was seen with views on the VOD and engagement. Comments, subscribers, followers, unique chatters, messages per minute, and viewer to chatter ratio all had relatively strong positive correlations with engagement. This shows audience participation and interaction is key to engaging viewers with the goal of turning a viewer into an active participant. It was found that subscriber-only chat disables a large portion of a channel’s viewers, limiting its overall engagement.

Implications and Recommendations

We take seriously the potential impact of improving user engagement strategies from not only a business perspective, but also as a possible source of learning for young game designers. While this paper has primarily focused on Singaporean Twitch viewers, many of these recommendations can be extended to other platforms and viewer demographics. We use knowledge gained from our observations to devise a number of potential strategies and improvements that can be made to increase viewer engagement. We later discuss these with the game design lecturer and a few gamers for comment and feedback. These suggestions have been built upon our own ideas and the ideas of the people we have discussed with. Throughout sections 4.1 and 4.2, we will attempt to provide a number of potentially helpful strategies that we believe can contribute to a more engaging and immersive viewing experience for various forms of stream media. This may then lead to increased enjoyment and gratification by the viewer. In 4.3, we reaffirm the importance of the streamer-to-viewer relationship and suggest that streamers who are serious about increasing the potential success of their stream should strive to develop a close relationship with their viewers.

Enhancing Viewer Engagement Strategies

Lastly, we found that the more a viewer engages with chat, the longer the viewer will stay in the stream. This last point can be assumed, however, it is important to constantly monitor it as the viewer behavior and stream environment can change over time. Any decrease in chat engagement must be countered by some of the previously mentioned engagement strategies to maintain vibrant viewer behavior.

Matching the mood or reactions of the broadcaster is again another form of distinct engagement, and we have found that even tracking the viewer’s cursor as it moves over the stream can have a positive effect. Although methods of tracking the cursor of the viewers can be quite intricate and development-heavy, this is an area where more technological engagement features can be developed.

We have already talked about rewarding engagement with viewers through fan-gate mechanics and prize giveaways, and how this brings positive effects. We also found that asking questions or seeking opinions from the viewers shows the most effectiveness. A direct call for an opinion or idea is a distinct act of engagement from the viewer to the broadcaster and less resourceful in the mind of the viewer.

The key concept drawn from our findings on engagement in live streaming is that more engagement states lead to better perceptions about the stream and what it is portraying. This, in turn, keeps the viewer wanting to come back for more. In light of this, it is recommended that all broadcasters attempt to keep the viewer as engaged as possible for as long as possible. This can be achieved in various ways.

Leveraging Peak Engagement Times

When popular consumers purchase a video game they find interesting, they are usually there to stay and engage with the stream. However, popular consumers are only a fraction of the total viewers. These consumers most likely live in a country with a time zone difference of more than 6 hours. As you can see, popular stream times for the host may not be convenient for many viewers. This ends up in viewers coming into streams and leaving because the streamer may not be on. In case someone is not familiar with how the hosts stream times appear to the viewers, an aggregate of viewer counts are analyzed in Figure 2. It has been divided into four graphs, each representing a 6-hour interval. Looking at the comparison, a slight increase of viewers can be seen during the 3rd and 4th graphs (afternoon and night in Singapore time). This gives a slight idea that nighttime is a suitable stream time for the majority of viewers. To further analyze this idea, it’s recommended to use the Simpson’s Paradox method on a larger dataset in the future.

Building Stronger Influencer-Viewer Relationships

In the context of live streaming, influencers are community leaders who often build relationships with their followers. As leaders/influencers often portray behaviors that they expect from their followers, it is essential that they themselves exhibit increased levels of interaction when cultivating relationships. Looking at our results on peak times and the previous section on viewer engagement strategies, the best time for such interaction is during broadcast at peak user times, or through off-air promotional materials to entice viewers to participate during peak times. An active chat significantly increases probability of future view return and interaction may boost inspiration of a creative idea for the content provider. Past interactions may also lead to deeper relationships, as is the case in a successful business deal with someone in your network compared to a stranger. An incentive system would benefit both influencers and viewers. In return for increased interaction at peak times, viewers may receive exclusive content or preferential treatment that the influencer can leverage to gauge interest in future activities.


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