| dc.contributor.author | Lu, Yang | |
| dc.description.abstract | Twitter is one of the most popular worldwide social networking services. It has more than 320 million monthly active users around the world. So it’s a very good way to discover what’s happening in the world and we can even get people’s opinions of some topics through their posts. Genetically modified food is one of the hottest topics all over the world. For the work of this paper, our aim is to determine people’s opinions concerning GMOs, but also interested in whether there are differences by gender. To achieve the goal, the idea is to capture a large set of Twitter feeds that all include a reference to GMOs, then carry out analytics on the tweets to classify them by gender, then carry out statistical tests aimed at identifying differences in perceptions by gender. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Perceptions of Genetically Modified Foods by Gender | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2016-10-25T20:49:09Z | |
| dc.date.available | 2016-10-25T20:49:09Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | http://hdl.handle.net/10365/25844 | |
| dc.subject.lcsh | Genetically modified foods -- Public opinion. | en_US |
| dc.subject.lcsh | Public opinion -- Sex differences. | en_US |
| dc.subject.lcsh | Twitter. | en_US |
| dc.subject.lcsh | Data mining. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Nygard, Kendall | |
