"You're liking it without reading it, aren't you?": The truth about pinned articles proven by data

"Another wonderful article today! You got another like, you know~"

As the gentle voice of the AI sister played in my head, I took a sip of coffee. Today, 40 days into starting note, I analyzed the data from an accountant's perspective regarding"the truth everyone knows but doesn't say out loud." I analyzed the data from an accountant's perspective.

In this article, I will confirm with cold, hard numbers the"common occurrences" that every note creator vaguely senses.

The surprising relationship between the pinned article "AI Sister" and the latest article "Claude 3.7"

AIお姉さん記事：274ビュー / 102スキ / スキ率37.23%
Claude 3.7記事：372ビュー / 13スキ / スキ率3.49%

The numbers that jump out at you first are quite extreme, aren't they?

"The most read article is not necessarily the most liked article" is the fact that emerges.

However, there is an even more surprising fact. In reality, my pinned article "AI Sister" has seen itslike rate improve over time.

＜AIお姉さん記事の時間経過による変化＞
初期（2025/2/12）: 読了数145, スキ数45, スキ率31.03%
現在（2025/3/6）: 読了数274, スキ数102, スキ率37.23%
変化: 読了数+89%, スキ数+127%, スキ率+6.20ポイント

General note articles tend to have their like ratesdecline as the reader base expands over time. However, this pinned article defies that common wisdom.

To solve this mystery, I asked two AIs to analyze it, and I also interpreted the numbers from my own perspective as an accountant.

The "liking without reading" phenomenon confirmed by data

From the analysis by two AIs and my own observations, a phenomenon that every note creator intuitively knows has been backed up by numbers. This behavioral pattern is close to what we call"apparent transaction increase" in accounting terms.

"Many people like pinned articles without actually reading them"

This was the key to solving the mystery of the abnormally high 37% like rate and why the like rate increases over time.

Tracing the flow of user behavior:

1. I like another user's article

2. The user who receives the notification visits my profile

3. The first thing they see is the pinned article

4. As a "return favor," theylike the pinned article without reading it

This"habit of liking without reading" is a natural flow in terms of note's interface design and behavioral psychology, and it is a"common phenomenon" that many creators experience daily. Perhaps you, who are reading this article, have also liked someone's pinned article without reading it?

In fact, my article"Is this a circular transaction?" which examined the mechanism of note, also achieved a high like rate of 23.12%, indicating that many users empathize with this phenomenon.

The "content effect" visible from the like rate of all articles

Analyzing the average like rate by article type reveals the following trends:

AIツール解説: 平均スキ率 13.00%（6記事）
キャラクター関連: 平均スキ率 14.74%（1記事）
技術的な記事: 平均スキ率 10.24%（1記事）
雑談・エッセイ: 平均スキ率 12.59%（2記事）
全体平均: 12.82%

Of course, return likes alone cannot explain the high like rate of 37%. The quality and relatability of the content itself also have a significant impact.

In particular, the emotionally appealing elements in article titles like "I want an AI to praise me!" are thought to evoke stronger empathy than simple technical explanation articles, leading to liking behavior as a result.

Visualizing article performance: Distribution of "Read count vs. Like rate"

When I plot the performance of all my articles on a scatter diagram, the characteristics of each article type become obvious. The horizontal axis represents the read count, and the vertical axis represents the like rate; the further to the top right, the more ideal the article is, being "widely read and having a high like rate."

Key points that can be read from this chart:

1. The anomaly of the AI Sister article (pinned article): With 274 reads, 102 likes, and a 37.23% like rate, it boasts an overwhelmingly higher like rate compared to other articles. The phenomenon of "being liked without being read" is clearly manifested.

2. Characteristics of the Claude 3.7 article: It achieved the top view count with 372 reads, but the like rate is only 3.49%. This is likely the result of spreading to a reader base that does not have the habit of pressing like, such as "passersby" who arrived via search traffic.

3. The meaning indicated by each of the four quadrants:

   • Top right (ideal engagement): The AI Sister article is positioned here, being read by many people while also receiving high praise

   • Top left (niche popular article): The "Is this circular trading?" article is strongly supported by a core fan base

   • Bottom right (information inflow type article): Like Claude 3.7, it is read as an information-providing type, but gets few likes

   • Bottom left (buried articles): Both read count and like rate are low; these are articles that have not yet been discovered

The red dashed line shows the overall average like rate of 12.82%, and whether an article is above this line indicates the degree of reader empathy. Since the size of the circle represents the absolute value of the number of likes, the magnitude of the influence of the AI Sister article can also be understood visually.

The trend shown by this scatter diagram strongly supports the "phenomenon of liking without reading" from the previous chapter. The difference in like rates between pinned articles (AI Sister) and non-pinned articles is particularly obvious.

Laws of engagement visible from titles and content

From AI analysis, several factors that influence engagement on note have emerged:

1. Emotional titles ("astonishing," "moved my heart") increase read counts

2. Titles indicating concrete methodologies ("~ techniques," "~ methods") tend to have higher like rates

3. Technical and information-based articles have many views but lower like rates

4. Content with strong personal experiences or playfulness leads to higher like rates

Combining these laws, a golden ratio of "emotion x concreteness x personal experience" comes into view.

Advanced "pinned article strategy": Is everyone doing it? Window-dressing techniques

For those who have read this far, let me share an even more advanced "pinned article utilization technique."

"Pin articles you want to collect likes on, and rotate them regularly"

This might be a strategy that many note creators are implicitly practicing. For example:

1. Strategy of pinning paid articles - By taking advantage of the "liking without reading" phenomenon and pinning a paid article, you can create the impression that "this article is highly rated" (when in reality, it is just being liked without being read).Readers may perceive it as "an article that many people have purchased and rated highly," which could increase their desire to purchase.

2. Regular rotation of articles you want to collect likes on - Pin a specific article for a certain period, and once it has collected enough likes, swap it with another article. In this way, it is possible to "distribute" likes evenly across multiple articles.

3. Increasing the value of stock articles - By periodically re-exposing high-quality past articles in the pinned position, you can maintain a state of "being liked even without being read" over a long period.

Pinning paid articles is a particularly interesting strategy. Since you can usually only read a portion of paid content for free, it is a perfect match for the "liking without reading" phenomenon. You can create a situation where, even if the content isn't read in detail, the number of likes steadily increases, truly "letting the numbers take on a life of their own."

From an accountant's perspective, this could be called "window-dressing techniques," but under the note system, it is a completely legitimate strategy. After all, the pinned article feature itself is meant to "showcase articles you want people to pay attention to."

The effort to maximize the "metric" of like counts is the same as "KPI optimization" in business, and could be called a smart strategy.

5 Practical Tips for note Creators

From this analysis, some hints for effective note management have emerged:

1. Choose pinned articles strategically — Pin emotional articles that gather the most engagement to maximize the efficiency of "reciprocal likes."

2. Fusion of "technical explanation × personal elements" — Instead of just listing information, weaving in the author's background and impressions improves the like rate.

3. Be active with likes during the initial phase of an article — Liking other users' content can be a trigger that creates a "cycle."

4. Add emotional elements and specificity to titles — Structures like "I want to...!" or "How to..." draw out high engagement.

5. Triggers to encourage comments — Including a question like "What do you think?" at the end of an article increases the comment rate

Conclusion: A strong mentality that doesn't care even if it's "not being read"

"Many people like pinned articles without reading them" is a fact that is ironic in a way, but perhaps it should be accepted as part of the note ecosystem.

What is important is not to get discouraged by this "maybe it's not being read" fact, but to continue providing content that is essentially valuable. From another perspective, the high like rate of pinned articles may mean they are playing a bookmark-like role as "articles I want to read someday.""articles I want to read someday" as a bookmark-like role.

Ultimately, rather than an attitude of "being satisfied with just likes," a sense of balance of "strategically utilizing the asset of a pinned article while pursuing essential value" is important.

To put it in a way befitting an accountant, perhaps one should prioritize "long-term assets like truly read articles" over "short-term revenue like the apparent number of likes." Even so, it is human nature to be genuinely happy when the likes on a pinned article increase."long-term assets like truly read articles" over "short-term revenue like the apparent number of likes."

What do you think? Do you see a similar phenomenon with your pinned articles? Please let me know in the comments section.

(I finished my coffee and finally finished writing the article. I look forward to likes and comments from all you analysis enthusiasts!)

"Hehe, that was a lovely analysis. Please cherish both your calm, accountant-like perspective and your honest, human feelings~"

Nodding at the AI lady's words, I gazed at the like button.