Title of your report

Your name

2021-01-11

• Tips for R Markdown
• Abstract
• Background
• Research Question
• Dataset
• Network Figure
• Method
• Results
• Discussion
• References

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Abstract

Overview of your research in a single paragraph.

Background

Existing research, debates, theoretical contexts, summary statistics or anything that will help you to claim that your research question and analysis strategy are important and original.

Research Question

Your research question: what do you want to indentify? You can start from an abstract statement and then introduce a verfiable research hypothesis. e.g. Are international players in Japanese soccer league better in their performance compared to domestic players? ~~~ One of the network metrics is crucial at identifying their performance.~~ Hence I validate whether such divergence does exist.

Dataset

Describe your dataset here. If your dataset is a network, you should give concrete explanation about how the dataset was collected, what the nodes and edges represent, and the number of nodes and edges.

Network Figure

Draw the network you have using any layout you like to. A better layout is the one showing representative / important global charateristics ( clustering, geographical distribution, and etc.) of your network. As shown bleow, please provide the entire code used to generate the figure.

require(igraph)
#> Loading required package: igraph
#> 
#> Attaching package: 'igraph'
#> The following objects are masked from 'package:stats':
#> 
#>     decompose, spectrum
#> The following object is masked from 'package:base':
#> 
#>     union
# plotting a simple ring graph, all default parameters, except the layout
g <- make_ring(10)
g$layout <- layout_in_circle
plot(g) 

Fig.1. Your figure caption.

Method

Here you should give mathematical definition of the measures (e.g. modularity) you are going to use, and verbal interpretation of what it means.

e.g. Given an undirected unweighted network A<?XML:NAMESPACE PREFIX = "[default] http://www.w3.org/1998/Math/MathML" NS = "http://www.w3.org/1998/Math/MathML" />A and the node characteristic vector cc, modularity QQ is defined as:

Q=12m∑i≠j(Aij−kikj2m)δ(ci,cj)Q=12m∑i≠j(Aij−kikj2m)δ(ci,cj)

where AijAij indicates the presence of a link between nodes ii and jj, mm is the number of edges, kiki is node ii’s degree, cici is node ii’s characteristic label, and δ(ci,cj)δ(ci,cj) is an indicator function satisfying:

δ(ci,cj)={0 when ci≠cj1 when ci=cj.δ(ci,cj)={0 when ci≠cj1 when ci=cj.

As a measure of homophily or assortative mixing, QQ becomes high as blahblah (Newman, 2018).

Results

Using tables, graphs or figures you should present the exact results you obtained.

Just in case, importing image files that were not generated using R:

Fig.2. Your figure caption

OR

plot(1:10)

Fig.3. Your figure caption.

Discussion

Here interpret the tables, graphs or figures you showed in the Results section.

What is the relevance of your findings?

e.g. According to theories in labor economics, relocation of workers to other countries only take place when such and such conditions are fulfilled. My finding suggests that it does hold / does not hold for the case of international players in J-Leage. This implies blah~ blah~

References

1. Newman, M. (2018). Networks. Oxford university press.

2. Fraiberger, S. P., Sinatra, R., Resch, M., Riedl, C., & Barabási, A. L. (2018). Quantifying reputation and success in art. Science, 362(6416), 825-829.