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Topics On Social Network Analysis: Short Courses & Samples Data Sets

topic on social networks with short courses links

Social Network Analysis  is a hot topic of research these days. There are many ways to explore the human behavior on Social Network (SN). Millions of users express their views and opinions freely about any topic. To capture users feedback, views SN is one of the easiest ways to get started. In the article, we will highlight some open research topics for researchers who are interested to research in the field of text analysis, a subdomain of Natural Language Processing (NLP). Topics on Social Network Analysis (SNA), short courses and sample data on SNA are key point of discussion.

We will also highlight some of the topics which are equally important for both Ph.D. and masters students to research. Before we get started, you must review most important research papers which all Social Network Analysis students should read.

  1. Collective dynamics of ‘small-world’ networks
  2. Random graphs with arbitrary degree distributions and their applications
  3. Finding and evaluating community structure in networks
  4. The Strength of Weak Ties
  5. Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality

Facebook is American online social platform launched in 2004. It has been changing in various sections due to user experience and recommendations given by a user’s. However, these suggestion and recommendation used by researchers in various research productivity.

Research in the field is still in progress, such as trigger the romantic relationship based on friends is one the hot topic. Various Public Access Application Programming Interface (API) is available to collect data. Of course, the data is in raw form; you can adopt different Machine Learning (ML) and NLP algorithm to predict human behavior’s.

“Some people use social network analysis to find “influencers”, people who have a higher degree of connectedness”

Similarly, on Twitter, a more organized community found. Twitter search and stream API provides user to collect public data. Companies invest in Social Networks (SNs) to collect quick opinions posted by users on their product to know the current market trends. It is the easiest way to collect millions of people feedback efficiently.

Medical behavior detection on Twitter is also an interesting topic these days. Different research activities have been conducted by researchers to collect related medical data. Detection of depression on the social network after analyzing user’s tweets, detection of affected areas geographically for early prevention’s of any disease have great importance. Similarly, problems such as Polio, Influenza, Dengue Virus need lot concentrations from a research point of view.

You may also read: How to write an effective PhD Motivation Letter

Researchers are working from a different field in SNA such as Mathematics, Management Science, Computer Science. Mathematicians are interested to know the how network change with the passage of time and which models implied to know the growth of the network. From Management point of view, researchers collecting crowd opinions to build new models to enhance the usability and user experience. Most of the work in the field of SNA people are working on sentimental analysis a field in NLP. Some hot topics in NLP are:

  • Understanding how networks change over time
  • Understanding how people form communities
  • Information diffusion among people in a network
  • Visualizing complex relationships
  • Identifying powerful and influential participants
  • Clustering of complex networks
  • Recommendation of interesting persons and resources
  • Terrorist identification
  • Privacy preservation
  • Privacy preservation

Sample Social Network Analysis Data Sets

Research can be conducted on already available data sets which are publicly available free to use. However, students also implement various API which is free to use to collect public data. Some data which are freely available to do different experiments you can use it via below links:

  1. Stanford Large Network Dataset Collection
  2. UCI Network Data Repository
  3. Interesting Social Media Datasets
  4. Network data
  5. Kevin Chai’s Homepage

You can also Google for more data collections by typing keywords such as:

  1. Konect
  2. Amick
  3. BGU Social Networks Security Research Group
  4. Barabasi
  5. CCNR
  6. Alex Arenas

Short Courses on Social Network Analysis

Short Course for SNA can help researchers to have deep knowledge of the current environment, algorithms and the technique which are helpful to solve different problems. We recommend Matthew Jackson’s Social and Economic Networks which is available on Coursera, is one of the best course to have knowledge related to SNA. It has covered most advanced topics related recent techniques which are helpful for experts.

However, applied Social Network Analysis in Python available on Coursera is helpful for users. It is helpful for those students who have some programming skills and can easily understand python syntax for visualizing, and information extraction from text using different ML and NLP algorithms.

Conclusion

There are many areas; we can explore using social network data. Because, problems are increasing on a daily basis due to the complexity of users. We have presented some domains related to effectively analyzing the social network data to generate quality research.

We recommend, if you are an early researcher, you must read some basic NLP practices used on text because using them, will help you to present raw data differently to solve the different problems. Machine Learning algorithms, however, have equal importance on raw text. With the passage of time, you will experience more problems and areas in the field of SNA.

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