We propose to analyze the level of recommendation and spreading in the sharing of scientific papers on Twitter to understand the interactions of communities around papers and to develop the “community of attention network” (CAN). In this paper, a pilot case study was conducted for the paper ‘Pharmacological Treatment of Obesity’ authored by Mancini and Halpern (Arquivos Brasileiros de Endocrinologia & Metabologia 46(5):497–512, 2002. 10.1590/S0004-27302002000500003), an extensive review of the criteria for evaluating the efficacy of anti-obesity treatments and derived pharmacological agents. The altmetric data was collected from Altmetric.com and the description information for each tweeter was extracted from their Twitter profiles. The data were analyzed with Microanalysis of Online Data perspective to investigate the formation of a CAN around this focal paper and the context of its formation. The studied article received 736 tweets from 134 different users with a combined exposure of more than 459,018 followers and a high level of spreading (67.26%) and recommendation (28.53%). The user’s bios information analysis of who shares the article indicate individual profiles focused on personal issues and strong civic and political engagement. Personal-professional and institutional tweeters of the national political scene are often mentioned in the tweets. In analyzing the content of the tweets, we note that the altmetric score of the paper is a result of its strategic use as an online activism resource and a digital advocacy tool used to mobilize stakeholders for awareness and support activities. This study and the contextual and network perspective it introduces may help to understand the social impact of publications by using altmetrics.

中文翻译：

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注意力网络社区：介绍替代度量的定性和对话视角

我们建议分析 Twitter 上科学论文分享中的推荐和传播水平，以了解围绕论文的社区的互动，并开发“关注网络社区”（CAN）。在本文中，对 Mancini 和 Halpern (Arquivos Brasileiros de Endocrinologia & Metabologia 46(5):497–512, 2002. 10.1590/S0004-220003, an) 撰写的论文“肥胖的药物治疗”进行了试点案例研究广泛审查评估抗肥胖治疗和衍生药物疗效的标准。altmetric 数据是从 Altmetric.com 收集的，每个推特用户的描述信息是从他们的 Twitter 个人资料中提取的。使用在线数据微观分析视角对数据进行分析，以研究围绕这篇焦点论文的 CAN 的形成及其形成的背景。所研究的文章收到来自 134 个不同用户的 736 条推文，总曝光超过 459,018 名关注者，传播（67.26%）和推荐（28.53%）水平很高。用户对谁分享文章的 bios 信息分析表明个人简介专注于个人问题以及强烈的公民和政治参与。推文中经常提到国家政治舞台上的个人专业和机构推特。在分析推文的内容时，我们注意到，该论文的 altmetric 分数是其作为在线激进主义资源和用于动员利益相关者进行意识和支持活动的数字宣传工具的战略用途的结果。这项研究及其引入的上下文和网络视角可能有助于通过使用替代度量来了解出版物的社会影响。