Methods: A Twitter-stream monitoring application has been developed using Python and the Tweepy library to collect data for this study and will capture posts associated with the aforementioned hashtags. This method has been trialed successfully in a previous North American focused project and will be expanded in this effort to capture a more global representation, including geolocation data when available. In the months immediately preceding the conference the Python scraper will retrieve nursing related tweets to populate a SQL database. Using Python and a natural language processing toolkit, the raw Tweets will be analyzed for trends and common themes. This analysis will include separating original Tweets from re-Tweets, assessment of tone using sentiment scores, and the identification of the most impactful Tweets and/or Tweeters in terms of volume and reach.
Results: The relative frequencies of the targeted hashtags will be evaluated over an initial two-week period allowing for refinement of the Python code to establish a robust tracking system. In past study this period typically produces several thousand tweets for the data set supporting efforts to capture a comprehensive near-real-time analysis of activity related to nursing on the Twitter platform. During this time, additions can be made to the tweet-set as needed, capturing emerging trends or campaigns. Data collection then continues for several months and in the weeks immediately preceding the conference a full suite of analytics, as previously detailed, is completed. When possible, the influence of world events, and/or the timing of publicized nursing campaigns are integrated into the analysis. The results are then translated using visual data mapping techniques to provide a comprehensive view of the data supporting new insights into the global reach and effectiveness of nursing on SM.
Conclusions:Nursing lacks a globally endorsed set of professional hashtags. While certain campaigns or initiatives have resulted in more focused messaging, the nature of SM does not permit ownership or control over popular tags such as #nurse or #nursing. This study will highlight the effectiveness of current SM efforts in nursing including a comparison of generic versus targeted postings or campaigns. SM is a key, albeit often overlooked, aspect of the emerging technologies that comprise our digital future. These media can be employed more effectively to deliver enhanced opportunities for collaboration and knowledge exchange, including the development of individualized personal learning networks to better prepare the profession for the future. Nursing organizations should continue to promote the importance of SM in the pursuit of global connectivity for the discipline and maximize the use of these tools in demonstrating the knowledge and critical contributions of nursing around the world.