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| − | ==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Multivariable Regression on tweet content vs Google Trends</strong></font></div></div>==
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| − | <p>With reference to trending topics on a particular day of a tweet, multivariate regression will be performed to relate trending topics to the popularity of a tweet (retweet, likes, etc). </p>
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| − | <p>The key variables that we intend to explore are elaborated in the table below:</p>
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| − | {| class="wikitable" width="70%"
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| − | ! Variable !! Importance
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| − | Retweets
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| − | || This measure shows how many times a particular tweet is being shared by followers. We think this is interesting because it highlights the willingness of an individual to share the tweet, increasing the probability that the tweet was interesting.
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| − | Url clicks
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| − | This measure shows how many times users actually click on the shortened link shared within a tweet. Given the succinct nature of a tweet, users who click on outgoing links are likely to find the tweet more interesting than other tweets, since clicking on the link would mean interrupting the "flowing" nature while reading the Twitter feed.
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| − | Likes
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| − | Compared to Url clicks and Retweets, this measure is the mildest, indicating that the user probably found the tweet interesting, but wasn't compelling enough to share.
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| − | Engagement Rate
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| − | A consolidated figure to illustrate how many people who see a particular tweet eventually interact with it (out of the total number of people who saw the tweet), in the following ways/forms:
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| − | *Link clicks
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| − | *Favourites
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| − | *Retweets
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| − | *Replies
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| − | *Embedded media clicks
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| − | *Detail expands
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| − | *Shared via email
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| − | *Permalink clicks
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| − | *User profile clicks
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| − | *Follows
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| − | Tweet Text
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| − | Although the effectiveness of jokes can be tough to evaluate from a linguistics perspective, our initial approach would be cross referencing the hashtags used in the tweet with Google Trends data (Searches & Events)
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| − | |}
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| − | <p>Giving a perspective on the important key variables that affects the popularity of a tweet will aid in the formulation of content that have higher penchant of being a popular tweet</p>
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| − | ==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Google Trends Correlation</strong></font></div></div>==
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| − | <p>While planning what content should be created, the team content team usually base it on gut feel, and usually the popular ones are accompanied when it is with regards to a big event in Singapore (eg. GE 2015). We want to incorporate the use of Google Trends to provide a more data-driven approach for SGAG in determining when and what content to publish. By analysing content consumption patterns of previous content around various types of events, future predictions can be forecast and appropriate content can be delivered at the appropriate timings.
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| − | </p>
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| | ==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Targeted Content</strong></font></div></div>== | | ==<div style="background: #232AE8; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Targeted Content</strong></font></div></div>== |
Revision as of 16:25, 17 April 2016
In the table below we outline the algorithms/techniques that we intend to execute for a particular objective.
| Objective |
Analytical Approach
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| Network analysis via Degree centrality, Betweenness centrality |
- Social Network Analysis
- Cluster Analysis
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| Plan what to publish based on characterisation of audience
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- Multivariable regression
- Cross reference of google trends data and content of tweet
|
Content created at SGAG is tailored for Singaporeans, and revolve around the milestones commonly encountered at different ages. For example, the typical 18 year old male Singaporean faces the prospect of enlistment into Basic Military Training (BMT), and would experience a mixture of emotions. SGAG takes milestone events like these makes humorous content on it. Below are the targeted age groups for SGAG, with some of the associated commonly met milestones:
| Age Group |
Milestone Content Topics
|
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18 - 21
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- Male: National Service (Basic Military Training), Relationship issues
- Female: Entry to University, Student Exchange Programme, Relationship issues, Social Night
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22 - 25
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- Male: ORD (End of National Service), Entry to University, Relationship issues, Social Night
- Female: Graduation from University, First Job, Colleagues
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26 - 34
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- Male: Graduation from University, First Job, Colleagues
- Female: Family, Having Kids
|
Content creation is also based on events that happen in Singapore. These are categorized into 2 types, expected and unexpected. Expected events include mainstream events like the National Day Parade, while unexpected events include train breakdowns. A more comprehensive list is given below:
| Event type |
Event Content Topics
|
|
Expected
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National Day Parade, SG50, SEA Games, Elections
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Unexpected
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Train breakdowns, different takes on Minister comments, Traffic accidents
|
By understanding the content consumption habits of SGAG's social media audiences through further analysis, SGAG will be able to better craft content publishing strategies to increase consumer base.
