library(ggplot2)
library(tidyr)
library(dplyr)
library(readr)
dataset <- read_csv("Students Social Media Addiction.csv")
dataset <- mutate(dataset, across(c(Gender, Academic_Level, Country, Most_Used_Platform, Affects_Academic_Performance, Relationship_Status), as.factor))
ggplot(dataset, aes(x = Avg_Daily_Usage_Hours, y = Sleep_Hours_Per_Night, color = Affects_Academic_Performance)) +
    geom_jitter(width = 0.2, alpha = 0.6) +
    scale_color_manual(values = c("Yes" = "#34eb46", "No" = "#fc0303")) +
    labs(title = "Effect of Social Media Use on Sleep and Academic Performance",
         x = "Average Time on Social Media per day(hours)",
         y = "Average Hours of Sleep per night(hours)",
         color = "Affects Academic Performance") +
    theme_minimal()

#this graph shows the effect of social media on student's sleep and performance in school. the red dots represent the students who are not affected academically by social media, while the green dots show that they are affected academically by social media. it can be seen from this graph that students get less sleep when they spend more than on social media, resulting in negative effects on academic performance.
ggplot(dataset, aes(Avg_Daily_Usage_Hours, fill = Affects_Academic_Performance)) +
  geom_bar(position = "dodge") +
  labs(title = "Effect of Social Media Use on Academic Performance",
    x = "Average Time Spent on Social Media per Day (hours)",
    y = "Number of Students",
    fill = "Affects Academic Performance"
  ) +
  theme_minimal()

#this bar graph shows the amount of students affected academically by social media... yeah its basically the same thing as the last graph... there's really no more to explain
ggplot(dataset, aes(x = Avg_Daily_Usage_Hours, y = Sleep_Hours_Per_Night, color = Addicted_Score)) +
  geom_point(size = 1.75, alpha = 0.65) +
  scale_color_gradient(low = "#96e0ff", high = "#011780") +
  labs(
    x = "Average Time Spent on Social Media per Day (hours)",
    y = "Sleep Hours Per Night",
    color = "Addiction Score",
    title = "Impact of Social Media on Sleep and Addiction"
  ) +
  theme_minimal()

#this scatterplot shows the effects of social media on students sleep and addiction score(to social media obv). as can be seen from this graph, the more students use social media, the more addicted they get, causing them to sleep less to satisfy this addiction.
ggplot(dataset, aes(x = Avg_Daily_Usage_Hours, y = Mental_Health_Score, color = Affects_Academic_Performance)) +
  geom_line(size = 1) +
  labs(
    x = "Average Use of Social Media per Day (hours)",
    y = "Mental Health Score",
    color = "Affects Academic Performance",
    title = "Effect of Social Media Use on Education and Mental Health"
  ) +
  theme_minimal()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

#as you can see, the more hours students spend on social media, the lower their mental health score. most of the students over 4 hours of daily social media usage tend to experience negative effects on their academic performance also. btw i dont know why the graph turned out like this...
ggplot(dataset, aes(x = Avg_Daily_Usage_Hours, y = Addicted_Score, color = Affects_Academic_Performance)) +
  geom_jitter(width = 0.2, alpha = 0.7) +
  labs(
    x = "Hours Spent Daily on Social Media",
    y = "Addiction Score",
    color = "Affects Academic Performance",
    title = "Effect of Social Media Usage on Education and Addiction"
  ) +
  theme_minimal()

#this graph shows the impact of social media on addiction and academic performance(dont mind how every graph is literally the exact same thing). theres really nothing more to say
dataset %>%
  group_by(Most_Used_Platform, Affects_Academic_Performance) %>%
  summarise(count = n()) %>%
  group_by(Most_Used_Platform) %>%
  mutate(prop = count / sum(count)) %>%
  ggplot(aes(x = Most_Used_Platform, y = prop, fill = Affects_Academic_Performance)) +
  geom_bar(stat = "identity", position = "fill") +
  labs(title = "Impact on Academic Performance by Most Used Platform",
       x = "Platform", y = "Proportion") +
  scale_y_continuous(labels = scales::percent) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
## `summarise()` has grouped output by 'Most_Used_Platform'. You can override
## using the `.groups` argument.

  theme_minimal()
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library(ggplot2)
ggplot(dataset, aes(x = Affects_Academic_Performance, y = Avg_Daily_Usage_Hours)) +
  geom_boxplot() +
  labs(title = "Daily Social Media Usage vs. Academic Performance Impact",
       x = "Affects Academic Performance", y = "Avg Daily Usage (hours)") +
  theme_minimal()

ggplot(dataset, aes(x = Avg_Daily_Usage_Hours, y = Sleep_Hours_Per_Night)) +
  geom_point(alpha = 0.8, color = "skyblue") +
  geom_smooth(method = "lm", se = FALSE, color = "black") +
  labs(title = "Social Media Usage vs. Sleep Hours",
       x = "Avg Daily Usage (hours)", y = "Sleep Hours per Night") +
  theme_minimal()
## `geom_smooth()` using formula = 'y ~ x'