Bartolome, Abigail Joy2018-08-092018-08-092018-08-08vt_gsexam:16657http://hdl.handle.net/10919/84528While many people enjoy hiking as a weekend activity, to many outdoor enthusiasts there is a hiking culture with which they feel affiliated. However, the way that these cultures interact with each other is still unclear. Exploring these different cultures and understanding how they relate to each other can help in engaging stakeholders of the trail. This is an important step toward finding ways to encourage environmentally friendly outdoor recreation practices and developing hiker-approved (and environmentally conscious) technologies to use on the trail. We explored these cultures by analyzing an extensive collection of tweets (over 1.5 million). We used topic modeling to identify the topics described by the communities of Triple Crown trails. We labeled training data for a classifier that identifies tweets relating to depreciative behaviors on the trail. Then, we compared the distribution of tweets across various depreciative trail behaviors to those of corresponding blog posts in order to see how tweets reflected cultures in comparison with blog posts. To harness metadata beyond the text of the tweets, we experimented with visualization techniques. We combined those efforts with ethnographic studies of hikers and conservancy organizations to produce this exploration of trail cultures. In this thesis, we show that through the use of natural language processing, we can identify cultural differences between trail communities. We identify the most significantly discussed forms of trail depreciation, which is helpful to conservation organizations so that they can more appropriately share which Leave No Trace practices hikers should place extra effort into practicing.ETDIn CopyrightHikersNatural language processingTopic analysisTwitterTechnology on the trailThesis