Summary and Reflection on Social Networking

To participate in IEMS5720 social networking is a great pleasure for me. Before I took apart in
this course, I used to think that social networking is more like reading story or report instead of
understanding theory and programming. However, Ms. Rosanna gives us a comprehensive introduction
to the concept, analysis and application of social networking which I never thought of. What’s more,
through several times of doing assignments, I have benefited a lot from this course.

Firstly, I understand what social media analytics is by acquiring relevant information in the
Internet. According to IEEE’s relevant definition, social media analytics is about making and assessing
information framework or tool to extract hidden key information from a large amount of
semi-structured and unstructured data collected in social media services in order to develop meaningful
and significant decision making (IEEE Intelligent Systems,2010). Apart from that, this process is
normally driven by the exact targets and requirements from desired practice. One feature that resembles
social media is that they both involve humanities and technologies. However, the other that doesn’t is
that social media analytics focuses more on “analysis” component such as natural language processing,
sentiment analysis & opinion mining algorithms, social network analysis and recommendation and
ranking.

Secondly, by finishing the two programming assignments, I think I learned a lot from this course.
The first programming assignment is sentiment analysis of comments on my blog, which belongs to
natural language processing category, and the other one encourages us to create a directed graph which
is able to represent the sociomatrix in order to understand and implement concepts such as density,
centrality and degrees etc. in the form of programming. By these two programming assignments, I have
learned basic concepts and mastered programming skills of social network comment analysis.

The last but not the least, it’s enjoyable and challenging to team up with other classmates to finish
the SDG 3 health and well-being. I used to think official data is more important than data from social
media platform since it can guarantee data’s accuracy. Nevertheless, through that process , I gradually
find data from social media more real-time and plentiful and can make a real difference if you
implement them properly.

Generally, taking part in this course is like a grand tour. I hope that one day I can implement those
techniques from this course into my work to help people to solve problems and make the world better.

References
1.D. Zeng, H. Chen, R. Lusch, and S.-H. Li. “Social Media Analytics and Intelligence”, IEEE
Intelligent Systems, vol. 25, no. 6, 13-16, 2010.