Amateur Footage: A Global Study of User-Generated Content

Data Collection and Analysis

The majority of content was not explicitly labeled as UGC, so we had to investigate many individual cases to confirm that it was user-generated content. This was achieved by cross-referencing content with items available on YouTube, Twitter, Facebook, or Instagram, as well as cross-referencing with photos and videos on the Reuters, AP, or Storyful portals. Because of these challenges, we had to ensure that the three of us were consistent in the way we analyzed the output. Therefore, the content analysis only began after we had reached a 95 percent agreement during pilot coding sessions. Even as the analysis was happening, there was continuous dialogue between all three researchers about examples that raised questions or issues. When the content’s origin was still unclear, we held a group discussion about the photo or video. Some of the content from more remote locations often looked at first glance like UGC, but under closer inspection was often shown to be footage captured by a local news channel with less sophisticated video equipment and then distributed by one of the main television news agencies to its clients. One of the best clues that a piece of content was filmed by a professional was the raw skill of the camera operator. Often, professional skills could be identified—such as the way the camera panned slowly across the action rather than the quick, jerky, or uneven movements associated with camera-phone video taken by amateurs. Ultimately, the researchers worked as hard as possible to ensure consistent and accurate coding, but we acknowledge there is undoubtedly a small margin of error resulting from the difficulty of coding unlabeled UGC.