library(tidyverse)
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library(igraph)                    
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Attaching package: 'igraph'

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library(visNetwork)              
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library(DT)
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library(plotly)
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library(broom)  
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friendships <- read_csv("friendships.csv")
Rows: 6972 Columns: 4
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (4): nominator, nominated, score, expected_score

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friendship_nodes <- read_csv("friendship_nodes.csv")
Rows: 84 Columns: 2
── Column specification ────────────────────────────────────────────────────────
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dbl (2): id, name

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  1. Nominator
friendships |> 
  group_by(nominator) |> 
  summarize(Mean = round(mean(score), 1)) |> 
  arrange(-Mean) |> 
  datatable(rownames = F,
            caption = 'Average friendship ratings given by each student')
  1. Nominated
friendships |> 
  group_by(nominated) |> 
  summarize(Mean = round(mean(score), 1)) |> 
  arrange(-Mean) |> 
  datatable(rownames = F,
            caption = 'Average friendship ratings given to each student')
friendship_model <- lm(expected_score ~ score, data = friendships)

tidy(friendship_model)
# A tibble: 2 × 5
  term        estimate std.error statistic  p.value
  <chr>          <dbl>     <dbl>     <dbl>    <dbl>
1 (Intercept)   0.0987   0.00739      13.4 3.22e-40
2 score         0.940    0.00352     267.  0       
glance(friendship_model)
# A tibble: 1 × 12
  r.squared adj.r.squared sigma statistic p.value    df logLik   AIC   BIC
      <dbl>         <dbl> <dbl>     <dbl>   <dbl> <dbl>  <dbl> <dbl> <dbl>
1     0.911         0.911 0.339    71178.       0     1 -2353. 4713. 4733.
# ℹ 3 more variables: deviance <dbl>, df.residual <int>, nobs <int>
friendships %>% 
  plot_ly(x = ~ score, y = ~ expected_score) %>% 
  add_markers() %>% 
  add_lines(y = fitted(friendship_model))
friends <- friendships |> 
  filter(score > 3) |> 
  select(nominator, nominated) |> 
  rename(from = nominator) |> 
  rename(to = nominated)
friends_network <- graph_from_data_frame(friends, friendship_nodes, directed = T)
friendship_nodes |> 
    mutate(named_friends = degree((friends_network), mode = "out")) |> 
  mutate(named_by_others= degree((friends_network), mode = "in")) |> 
  mutate(popularity = named_by_others - named_friends) %>% 
  select(name, named_friends, named_by_others, popularity) |> 
  datatable(rownames = F)
friendship_nodes |> 
    mutate(named_friends = degree((friends_network), mode = "out")) |> 
  mutate(named_by_others= degree((friends_network), mode = "in")) |> 
  plot_ly(x = ~named_friends) %>% 
  add_histogram() %>% 
  layout(title = "How Many Friends Students Named")
reciprocity(friends_network, mode = "ratio")
[1] 0.5205479
friendship_nodes |>  
  mutate(group = membership(infomap.community(friends_network))) %>% 
  visNetwork(friends, main = "Network of student friendships") %>% 
  visIgraphLayout(layout = "layout_with_kk") %>% 
  visEdges(arrows = "to") %>% 
  visOptions(highlightNearest = T, nodesIdSelection = T)
Warning: There was 1 warning in `mutate()`.
ℹ In argument: `group = membership(infomap.community(friends_network))`.
Caused by warning:
! `infomap.community()` was deprecated in igraph 2.0.0.
ℹ Please use `cluster_infomap()` instead.

```