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'发生了什么?' 对 Twitter 上与脑震荡相关的交通内容的分析。

'What's happening?' A content analysis of concussion-related traffic on Twitter.

机构信息

School of Physiotherapy, University of Otago, Dunedin, New Zealand.

出版信息

Br J Sports Med. 2012 Mar;46(4):258-63. doi: 10.1136/bjsm.2010.080341. Epub 2011 Mar 15.

Abstract

BACKGROUND

Twitter is a rapidly growing social networking site (SNS) with approximately 124 million users worldwide. Twitter allows users to post brief messages ('tweets') online, on a range of everyday topics including those dealing with health and wellbeing. Currently, little is known about how tweets are used to convey information relating to specific injuries, such as concussion, that commonly occur in youth sports.

OBJECTIVE

The purpose of this study was to analyse the online content of concussion-related tweets on the SNS Twitter, to determine the concept and context of mild traumatic brain injury as it relates to an online population.

STUDY DESIGN

A prospective observational study using content analysis.

METHODS

Twitter traffic was investigated over a 7-day period in July 2010, using eight concussion-related search terms. From the 3488 tweets identified, 1000 were randomly selected and independently analysed using a customised coding scheme to determine major content themes.

RESULTS

The most frequent theme was 'news' (33%) followed by 'sharing personal information/situation' (27%) and 'inferred management' (13%). Demographic data were available for 60% of the sample, with the majority of tweets (82%) originating from the USA, followed by Asia (5%) and the UK (4.5%).

CONCLUSION

This study highlights the capacity of Twitter to serve as a powerful broadcast medium for sports concussion information and education.

摘要

背景

Twitter 是一个快速发展的社交网络平台(SNS),全球约有 1.24 亿用户。Twitter 允许用户在线发布简短的消息(“推文”),内容涵盖从日常话题到健康和幸福等各个方面。目前,人们对如何利用推文来传递与特定伤害(如在青年运动中常见的脑震荡)相关的信息知之甚少。

目的

本研究旨在分析 SNS Twitter 上与脑震荡相关的推文的在线内容,以确定与在线人群相关的轻度创伤性脑损伤的概念和背景。

研究设计

使用内容分析法进行前瞻性观察研究。

方法

2010 年 7 月,使用 8 个与脑震荡相关的搜索词,对 Twitter 流量进行了为期 7 天的调查。从确定的 3488 条推文中,随机选择了 1000 条推文,并使用定制的编码方案进行独立分析,以确定主要内容主题。

结果

最常见的主题是“新闻”(33%),其次是“分享个人信息/情况”(27%)和“推断的管理”(13%)。在样本中,有 60%的人提供了人口统计学数据,大多数推文(82%)来自美国,其次是亚洲(5%)和英国(4.5%)。

结论

本研究强调了 Twitter 作为运动性脑震荡信息和教育的强大广播媒介的能力。

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