Cohen Samuel A, Tijerina Jonathan D, Amarikwa Linus, Men Clara, Kossler Andrea L
Stanford University School of Medicine, Stanford, CA, USA.
Aesthet Surg J. 2022 Apr 12;42(5):NP351-NP360. doi: 10.1093/asj/sjab429.
Plastic surgeons are increasingly turning to social media to market their services. The newly released Twitter Academic Research Product Track (TARPT) database provides free, customizable analysis of keywords that are included in tweets on the Twitter platform. The TARPT tool may provide valuable insight into public interest in cosmetic surgery procedures.
The aim of this study was to determine TARPT's utility in tracking and predicting public interest in cosmetic surgery procedures and to examine temporal trends in tweets related to cosmetic facial and body procedures.
The TARPT tool was used to calculate the total number of tweets containing keywords related to 10 facial cosmetic procedures and 7 cosmetic body procedures from 2010 to 2020. Annual volumes for respective procedures were obtained from annual statistics reports of The Aesthetic Society from 2010 to 2020. Tweet volumes and procedure volumes were compared by univariate linear regression, taking P < 0.05 as the cutoff for significance.
Variations in tweet volume were observed. Univariate linear regression analysis demonstrated statistically significant positive correlations between tweet volumes and procedure volumes for 7 search terms: "eyelid lift," "facelift," "lip injections," "mastopexy," "butt lift," "butt implants," and "liposuction." Many procedure-related keywords were not significant, demonstrating the importance of careful selection of Twitter search terms.
The TARPT database represents a promising novel source of information for plastic surgeons, with the potential to inform marketing and advertising decisions for emerging trends in plastic surgery interest before these patterns become apparent in surgical or clinical volumes.
整形外科医生越来越多地转向社交媒体来推销他们的服务。新发布的推特学术研究产品追踪（TARPT）数据库提供了对推特平台上推文中包含的关键词的免费、可定制分析。TARPT工具可能会为公众对整形手术的兴趣提供有价值的见解。
本研究的目的是确定TARPT在追踪和预测公众对整形手术的兴趣方面的效用，并研究与面部和身体整形手术相关推文的时间趋势。
使用TARPT工具计算2010年至2020年期间包含与10种面部整形手术和7种身体整形手术相关关键词的推文总数。从美国美容整形外科学会2010年至2020年的年度统计报告中获取各手术的年度手术量。通过单变量线性回归比较推文量和手术量，以P<0.05作为显著性临界值。
观察到推文量的变化。单变量线性回归分析显示，7个搜索词的推文量与手术量之间存在统计学上显著的正相关：“提眉术”、“面部提升术”、“唇部注射”、“乳房上提术”、“丰臀术”、“臀部植入物”和“抽脂术”。许多与手术相关的关键词并不显著，这表明仔细选择推特搜索词的重要性。
TARPT数据库对整形外科医生来说是一个很有前景的新信息来源，有可能在整形手术兴趣的新兴趋势在手术或临床手术量中显现出来之前，为营销和广告决策提供参考。
