TidyTuesday: Reddit Comment Counts - SOFI vs IONQ

Comparing daily Reddit discussion volume for SOFI and IONQ across investment subreddits with ggplot2

Overview

This week’s TidyTuesday explores social media attention as a market signal by comparing Reddit discussion volume for two US stocks: SOFI (SoFi Technologies) and IONQ (IonQ Inc.). Using the same dataset as the companion MakeoverMonday post, we visualize comment counts from investment-focused subreddits using ggplot2.

Data

library(tidyverse)
library(scales)
library(glue)
library(patchwork)

data_dir <- file.path(getwd(), "data")

daily <- read_csv(file.path(data_dir, "reddit_daily_counts.csv"),
                  show_col_types = FALSE) |>
  mutate(date = as.Date(date))

posts <- read_csv(file.path(data_dir, "reddit_posts.csv"),
                  show_col_types = FALSE) |>
  mutate(date = as.Date(date))

by_sub <- read_csv(file.path(data_dir, "reddit_by_subreddit.csv"),
                   show_col_types = FALSE)

# 投資関連サブレディットのみフィルタ
invest_subs <- c(
  "wallstreetbets", "stocks", "investing", "StockMarket", "options",
  "SOFIstock", "sofi", "IonQ", "Superstonk", "Pennystock",
  "premarketStockTraders", "TeamRKT", "Webull"
)

posts_f <- posts |> filter(subreddit %in% invest_subs)

daily_f <- posts_f |>
  group_by(date, symbol) |>
  summarise(
    post_count = n(),
    total_comments = sum(num_comments, na.rm = TRUE),
    total_score = sum(score, na.rm = TRUE),
    .groups = "drop"
  ) |>
  arrange(date, symbol)

cat(glue("Investment subs: {nrow(posts_f)} posts | ",
         "Range: {min(daily_f$date)} ~ {max(daily_f$date)}"))

Investment subs: 189 posts | Range: 2026-02-01 ~ 2026-02-15

Visualizations

1. Daily Comment Count Comparison

colors <- c("SOFI" = "#6366f1", "IONQ" = "#f59e0b")

p1 <- ggplot(daily_f, aes(x = date, y = total_comments, fill = symbol)) +
  geom_col(position = position_dodge(width = 0.8), width = 0.7) +
  scale_fill_manual(values = colors) +
  scale_x_date(date_labels = "%m/%d", date_breaks = "2 days") +
  scale_y_continuous(labels = comma) +
  labs(
    title = "Daily Reddit Comment Count: SOFI vs IONQ",
    subtitle = "Investment subreddits only (r/wallstreetbets, r/stocks, r/investing, etc.)",
    x = NULL,
    y = "Total Comments",
    fill = "Ticker",
    caption = "Source: Reddit public JSON API"
  ) +
  theme_minimal(base_size = 13) +
  theme(
    legend.position = "top",
    plot.title = element_text(face = "bold"),
    panel.grid.minor = element_blank()
  )

p1

2. Post Count (Threads Created)

p2 <- ggplot(daily_f, aes(x = date, y = post_count, fill = symbol)) +
  geom_col(position = position_dodge(width = 0.8), width = 0.7) +
  scale_fill_manual(values = colors) +
  scale_x_date(date_labels = "%m/%d", date_breaks = "2 days") +
  labs(
    title = "Daily Reddit Post Count: SOFI vs IONQ",
    x = NULL,
    y = "Number of Posts",
    fill = "Ticker"
  ) +
  theme_minimal(base_size = 13) +
  theme(
    legend.position = "top",
    plot.title = element_text(face = "bold"),
    panel.grid.minor = element_blank()
  )

p2

3. Engagement Ratio (Comments per Post)

daily_f <- daily_f |>
  mutate(comments_per_post = round(total_comments / pmax(post_count, 1), 1))

p3 <- ggplot(daily_f, aes(x = date, y = comments_per_post, color = symbol)) +
  geom_line(linewidth = 1) +
  geom_point(size = 2.5) +
  scale_color_manual(values = colors) +
  scale_x_date(date_labels = "%m/%d", date_breaks = "2 days") +
  labs(
    title = "Engagement Ratio: Comments per Post",
    subtitle = "Higher ratio = more concentrated discussion per thread",
    x = NULL,
    y = "Comments / Post",
    color = "Ticker"
  ) +
  theme_minimal(base_size = 13) +
  theme(
    legend.position = "top",
    plot.title = element_text(face = "bold"),
    panel.grid.minor = element_blank()
  )

p3

4. Subreddit Breakdown

by_sub_f <- by_sub |>
  filter(subreddit %in% invest_subs) |>
  mutate(subreddit = fct_reorder(subreddit, total_comments, .fun = sum))

p4 <- ggplot(by_sub_f, aes(x = total_comments, y = subreddit, fill = symbol)) +
  geom_col(position = position_dodge(width = 0.7), width = 0.6) +
  scale_fill_manual(values = colors) +
  scale_x_continuous(labels = comma) +
  labs(
    title = "Comment Volume by Subreddit (14 days)",
    x = "Total Comments",
    y = NULL,
    fill = "Ticker"
  ) +
  theme_minimal(base_size = 13) +
  theme(
    legend.position = "top",
    plot.title = element_text(face = "bold"),
    panel.grid.minor = element_blank()
  )

p4

5. Combined Panel

(p1 / p3) +
  plot_annotation(
    title = "Reddit Discussion Activity: SOFI vs IONQ",
    subtitle = "Feb 2026 | Investment subreddits only",
    theme = theme(
      plot.title = element_text(size = 16, face = "bold"),
      plot.subtitle = element_text(size = 12, color = "gray50")
    )
  )

Key Findings

1. SOFI dominates Reddit discussion volume – both in total comments and daily post count, reflecting its broader retail investor base and active dedicated communities (r/SOFIstock, r/sofi).
2. IONQ has lower volume but engagement spikes align with news catalysts and earnings events.
3. Engagement ratio (comments per post) reveals “heat” – when a few posts attract many comments, it signals concentrated attention that may precede price moves.
4. Subreddit distribution shows ticker-specific subs dominate volume, while r/wallstreetbets contributes fewer but higher-engagement threads.

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This post is part of the TidyTuesday weekly data visualization project.

CautionDisclaimer

This analysis is for educational and practice purposes only. Reddit comment counts and discussion metrics are based on publicly available data and may not represent complete or current information. This does not constitute investment advice.