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This paper introduces an agent-based model to study citation behavior. While I found the topic of the paper to be of significant interest and I didn’t spot any significant inaccuracies in the paper, I also found the paper challenging to understand. Below I summarize the difficulties I had in understanding the paper.

The Introduction section goes into considerable technical detail. The paragraph starting with “The model is relatively simple” and the subsequent paragraphs are rather detailed and technical, making them hard to follow. My suggestion would be to introduce the model in a more accessible and less detailed way in the Introduction section.

The use of terms such as ‘agent’, ‘fitness’, ‘in-degree’, and ‘out-degree’ makes the paper hard to read. Terms such as ‘article’, ‘quality’, ‘number of citations’, and ‘number of references’ are much more intuitive, so I would suggest to use these terms instead of the more abstract terminology that is currently used. Some terminological explanation is provided in Section 4.3. However, since this is explanation is provided at the end of the paper, it is of little use for readers. The term ‘neighborhood’ also needs to be defined.

In Section 4.2, I don’t understand the equation for Score_R. This equation requires more explanation.

It is not entirely clear to me in which order the paper is supposed to be read. I assumed the Materials and Methods section is supposed to be read before the Results section. However, this led to some confusion. For instance, the sj dataset is mentioned in the Materials and Methods section (Section 4.5), but is introduced in the Results section.

In the Results section, the font size in the figures is very small, making it difficult to read the figures.

The Results section presents clustering coefficients. The relevance of these clustering coefficients is not clear to me. What do we learn from them?

Competing interests

The author declares that they have no competing interests.