Deep Dive into Text Data — Label Behavior & Content Patterns

By abhishek.verma75000 · April 26, 2026

Analyzed 500 text records to understand how content structure, length, and patterns vary across two categories: intentional and unintentional.

The distribution of aaa label categories across the 500 records has been visualized in both a bar chart and a pie chart, giving you a clear view of how each category is represented in the dataset.

The analysis compared average text lengths between the two aaa label categories. A bar chart and data table were generated showing the average character counts for each category, making it easy to see which label tends to have longer or shorter text entries.

The 'intentional' category shows the greatest variance in text length, with a variance of 17,394,083 and a standard deviation of 4,171 characters. This suggests significant content inconsistency within that category compared to others. Two visualizations were generated: a box plot showing the text length distribution across all aaa label categories, and a bar chart comparing the variance values side by side.

The analysis produced two visualizations comparing text lengths across aaa label categories. A box plot shows the full distribution of text lengths (including outliers) for each label, and a bar chart displays the average text length per category — making it easy to spot which label contains the longest entries. Based on the charts generated, you can visually identify the category with the tallest bars and widest spread as having the longest text entries.

Yes, very short text entries (≤922 characters, bottom 25%) disproportionately belong to the 'unintentional' label. Among the 125 shortest entries, 92.8% are labeled 'unintentional' compared to just 71.4% across all 500 records — a difference of +21.4 percentage points. Conversely, 'intentional' entries are underrepresented in short texts (7.2% vs 28.6% overall). Two charts were generated: a grouped bar chart comparing label distributions between short texts and all texts, and a box plot showing text length distributions by label.

There is a notable difference in average word count between the two aaa label groups. Intentional texts average 714.3 words per text, while unintentional texts average just 303.7 words — meaning intentional texts are more than twice as long on average. A bar chart and data table have been generated to visually compare these two groups.

A bar chart and data table were generated showing how the average number of sentences per text varies across each aaa label category. The visualization makes it easy to compare which labels tend to have longer or shorter texts based on sentence count.

Using the 3×IQR method, 11 extreme outliers were identified out of 500 text entries. The analysis set the extreme outlier threshold at 11,360 characters (upper bound), meaning any text longer than this was flagged. Two visualizations were generated: a box plot showing text length distribution by label with the outlier threshold marked, and a scatter plot highlighting all 11 extreme outliers colored by their label.

The analysis reveals a highly right-skewed text length distribution across 500 documents. Most texts are relatively short, but a long tail of lengthy documents pulls the mean (2,819 chars) well above the median (1,832 chars). Three visualizations were generated: a histogram showing the full distribution with a median marker, a bar chart of content size clusters, and a box plot breaking down lengths by label.

Yes, the median text length is significantly different between the two labels. Intentional texts have a median length of 3,503 characters, while unintentional texts are much shorter at 1,334 characters — a difference of 2,169 characters (about 163% longer). This substantial gap strongly suggests structural content differences between the two categories.

Yes, the analysis successfully examined whether average word length differs by label category. Two visualizations were generated: a box plot showing the distribution of average word lengths for each label, and a bar chart displaying the mean word length per label. These charts reveal how word length varies across different content categories, which can indicate differences in content complexity.

The analysis calculated the 25th, 50th, 75th, and 95th percentile text lengths for each label. Intentional texts are consistently much longer than unintentional ones at every percentile. A grouped bar chart and data tables were generated to visualize these differences clearly.

Yes, text length does provide meaningful separation between the two label categories. Intentional texts average around 4,836 characters (median: 3,503), while unintentional texts are significantly shorter at an average of 2,011 characters (median: 1,334). Two visualizations were generated — a histogram showing the overlapping distributions with the optimal threshold marked, and a box plot comparing the spread of text lengths per category.

The analysis examined how the ratio of uppercase to lowercase characters differs between aaa label groups. Two visualizations were generated: a box plot showing the distribution of uppercase/lowercase ratios for each label group, and a bar chart displaying the mean ratio with standard deviation error bars. These charts reveal how consistently (or variably) each group uses capitalization relative to lowercase text.

Yes, the analysis examined whether special characters and numbers in text correlate with the 'aaa label' categories (intentional vs. unintentional). Two visualizations were produced: a grouped bar chart comparing average special character and number counts per label, and a box plot showing the distribution of special character ratios across both labels. The dataset contains 143 'intentional' and 357 'unintentional' text samples.

The analysis successfully produced visualizations and data tables examining near-duplicate texts across different aaa label categories. Two charts were generated: one showing the distribution of records across all aaa label categories, and another summarizing near-duplicate groups found at different matching granularities (exact, 200-char, 100-char, and 50-char prefix). Additional data tables were also produced to support the findings.