This study assumes that television is expanding to various devices and platforms by 'mediatization of media' phenomena and is minutely percolating to everyday life. Especially, as personal mobile devices, which can be viewed while in motion, started t...
This study assumes that television is expanding to various devices and platforms by 'mediatization of media' phenomena and is minutely percolating to everyday life. Especially, as personal mobile devices, which can be viewed while in motion, started to be utilized as secondary screens, previously home-based television is changing into a fluctuating network that interlocks viewing functions with other media. Above all, OTT (Over-the-top) service, a television platform that serves as a widely used internet video service, is quickly changing viewing environments with an internal logic distinct from the previous television environment.
This study investigates the flux of viewing consisting of internal OTT service logic and viewing experience via OTT service in a smartphone, a secondary television screen, by developing and applying a new research method. As people can view television broadcasts from various internet video services in real time, it is important to comprehend the differentiated viewing pattern and flux of viewing television by personalized mobile devices in a new methodology.
The television viewer has been considered an audience concept, and data has been collected by a survey based on recall or self-reported mechanisms. However, existing methods have limitations because of strengthened audience autonomy and control of various factors such as viewing patterns, viewing time, and usage route as it is possible to view television by internet video services and watching through personalized devices is increasing. Most of all, it is difficult for a respondent to recognize or recall certain media actions separately from behavior of complex media activities. Moreover, measurement accuracy of survey or questionnaire methods commonly used for theory driven data is very difficult to confirm. The problem of audience studies rests in their inconsistent results affected by respondents, dates of research and subjects. Survey inaccuracies through insufficient respondent recall can occur when complex media circumstances are not considered in the research methodology.
Perceiving this conundrum, this study suggests a new method that incorporates a respondent’s smartphone as a device for tracking viewing patterns to collect respondents’ usage data in natural daily environments.
Concretely, we developed a viewing pattern tracking application by embedding custom logging functions into an existing OTT service application that can accurately track individual viewing activities over time via a smartphone as a tracking device. We modified an OTT service application ‘tving’ and collected log data of viewing records of eleven participants for a month, and collected GPS coordinates of viewing events that matches data to track viewing while in motion. In addition, to interpret the context and experience that cannot be read from log data, we secured in-depth interview and FGI as quality datum.
The research results are as follows. First, there were differences varying from four to eight times between the degree of viewing (duration) collected from application compared to recall. Therefore, it is confirmed that the amounts of viewing according to respondent recall is very distinct from actual amounts tracked by the application. It can also be inferred that viewing activity and media usage from a single device can be integrated.
Second, results showed that respondents watch in all time periods by micro-coordinating viewing time via smartphones. In addition, it was found that respondents tended to sleep late due to viewing after midnight. This indicates that a new experience of viewing television influenced the rhythm of everyday life.
Third, viewing while moving revealed a very short viewing pattern as smartphone users are sensitive to wireless data usage. Viewing in places such as transportation systems, work places and university campuses is directly connected with economic problem, so the viewing time is not significant even though viewing events existed. Viewing while moving mostly consisted of DMB or stored content, and tving was used as an Electronic Program Guide (EPG). Most viewing via tving occurred at home, and this study explained the phenomena as ‘domesticated viewing while moving’ inside the house or domicile.
Fourth, most viewing involved live broadcasts among various content types (live broadcasts, VODs, advertisements, previews, short clips) as they easily avoid advertisements. Compared with the entirety of viewage, advertisements were the least viewed content. Significantly, awareness between live broadcast and VOD was extremely limited. We inferred that this result can be due to the internal media logic of an OTT service to provide television channels and VODs equally. Traditional television programs were organized linearly in terms of time, but OTT service transform content into units of video or image, and the flux of television is modularized as 'contents of content'. Therefore, respondents found very few differences. We interpreted this result as follows: the previous flux of television was linearly arranged with time, but OTT service is blurred as to time-schedule and synchronized programs by adducing channel and unit content, influencing cognition and viewing behavior.
Fifth, examining viewing patterns by content type, respondents tend to prefer entertainment content in terrestrial broadcasting and drama content in cable broadcasting. Certain terrestrial entertainment programs are repeated four to six times per day through cable channels and are located in the main page of OTT service daily. The main page of OTT service provides content such as live broadcast or rerun regardless of the type of content, and assuredly frequency influences respondent selections. OTT service fluidly arrange content depending on the flux of viewing, and the interface that considers the flux of viewing can be effected as reflecting a band-wagon effect of viewing.
Sixth, the characteristics of viewing activity via OTT service of smartphone can be conceptualized by mosaic viewing, a viewing segmented by seconds. Especially, when considering a respondent viewing via a smartphone or single media device, we confirmed that channel switching and task switching frequently occurred within a few seconds. However, this phenomenon was different from channel zapping via remote control.
This study is unique in its investigation and application of a new method.
First, we confirmed symptoms and phenomena that smartphones readjust the rhythm of daily life as they are utilized as a secondary screen, by analyzing specific, not theoretical, log data by detecting behavioral aspects of viewing experience by units measured in seconds.
Second, we developed a natural observation method using a common mobile device of the participant, smartphone, as a log acquisition tool. This study tracked the usage of a certain OTT service, but the method can be used as an extended data acquisition method in studies that consider experience and usage of a personalized mobile device.
Third, unlike traditional social scientific methods into which quantitative research and qualitative research are divided, this study integrated and analyzed quantitative and qualitative methods. It is becoming more difficult to generalize the concept of the consumer as an audience by measuring explicit factors in complex media environments. Rather than generalizing complicated media activity by applying unsuitable statistical methods, we inquired into a new methodology that focuses on analysis and consideration of the circumstances and context of the audience as well as classification and interpretation of an analytical system.