Scroll while AI works

The @scrollwhileaiworks account has 34,400 followers, demonstrating a substantial audience base. Its content achieves an average of 1,814,080 views per video, indicating strong reach across its video library. The account generates 2,200,000 total likes, resulting in an engagement rate of 0.95%, reflecting consistent audience interaction relative to its follower count.

The @scrollwhileaiworks account demonstrates a strong presence with 34,400 followers, which contributes to its high average likes per video (15,742). This suggests that each video is widely appreciated, as the sheer volume of likes indicates broad audience appeal. However, the overall engagement rate of 0.95% appears relatively low compared to the likes per video. This discrepancy may stem from the calculation method, which likely factors in all engagement types (likes, comments, shares) relative to the follower base. For instance, 15,742 likes alone would represent approximately 45.7% engagement if calculated as (likes / followers), but the 0.95% rate implies a broader average across all engagement actions, highlighting that while likes dominate, other interactions (comments and shares) are less frequent relative to the follower count. Audience interaction patterns reveal a focus on likes as the primary engagement metric, with comments averaging 210 per video and shares at 1,279. These figures suggest that while the audience is actively liking content, there is less organic discussion or content redistribution. The relatively low comment count compared to likes may indicate that viewers prefer passive engagement over dialogue, or that the content is more observational than participatory. Shares, though substantial, are still lower than likes, which could reflect a preference for personal interaction over sharing content. The overall engagement rate of 0.95% underscores that while the account has a large following, the depth of interaction remains limited, potentially signaling opportunities to foster more meaningful audience participation. The metrics collectively indicate that the content resonates strongly with viewers in terms of visibility and approval, as evidenced by the high likes per video. However, the low engagement rate and moderate comments/shares suggest that the content may not be driving deeper audience involvement. This could imply that the audience is primarily consuming content rather than engaging in discussions or sharing it widely. To enhance resonance, the account might explore strategies to encourage more comments (e.g., prompting questions or calls to action) or incentivize shares through creative hooks or community-building efforts. The high follower count also means that even small increases in comments or shares could significantly impact the overall engagement rate.

Engagement Quality Analysis

Median-based metrics that resist fake virality and outliers.

@scrollwhileaiworks prioritizes content centered on workplace culture and humor, as evidenced by its top hashtags. The account heavily utilizes #fyp (12x) to target trending content, while #officehumor (11x) and #officetok (7x) dominate, indicating a focus on relatable, humorous takes on office environments. Related hashtags like #office (7x), #corporate (7x), and #corporatelife (7x) further reinforce this theme, suggesting a strategic emphasis on corporate life and workplace dynamics. The inclusion of #worktok (7x) and #worklife (6x) aligns with broader trends in work-related content, positioning the account within niche communities interested in office culture. The hashtag strategy demonstrates thematic consistency by clustering around office-centric humor and corporate experiences, with #fyp serving as a primary driver for virality. However, the lower usage of hashtags like #viral (6x) and #marblism (6x) suggests less emphasis on broader trends or specific subcultures. The repetition of similar hashtags (e.g., #corporate and #corporatelife) may aim to reinforce brand identity within the office humor niche, while the absence of primary content category data limits deeper insights into visual or structural content strategies.

Video Duration Breakdown

Original Sound Usage

Percentage of videos using the creator's own audio