General Academic Paper (refereed paper)

The Impact of Reference Information and Psychological Factors on Media Viewing Behavior: An Experimental Study
Kazumasa MORI1 and Tomoko OE2
1Member of SGB, Associate Professor, Institute for Excellence in Educational Innovation, Chiba University(Address: 263-8522, Yayoi-Cho, 1-33, Inage-ku, Chiba, Japan)
E-mail: mori@faculty.gs.chiba-u.jp
2Non-Member of SGB, Professor, Dept. of Psychology, Teikyo University(Address: 192-0395, Otsuka, 359, Hachiouji City, Tokyo, Japan)
E-mail: tom-oe@main.teikyo-u.ac.jp

In this study, we examined the factors influencing viewing preferences among Japanese university students using experimental methods focusing on television and video streaming services (YouTube). Specifically, we presented participants with fictional program content accompanied by a pre-announcement andexperimentally inquired about their viewing preferences. We analyzed the impacts of media platform content tone, reference information, gender, and television viewing time on viewing preferences. Our statisticalanalysis yielded three key findings. First, we determined that reference information enhances viewing preferences for participants who watch television for longer periods, but only when the content tone aligns withthe positive or negative attributes of the reference information. Second, we found no significant differencesin viewing preferences based on media platform within the scope of this study. Third, we observed nodifferences in viewing preferences based on gender within the study's scope. These findings offer fundamental insights into information dissemination methods relevant to practical applications such as crisis
management and suggest avenues for future research.
Key Words : Media Viewing Preference, Reference Information, Crisis Management, Public Relations

with content conditions finely detailed. Basic andhighly applicable research in experimental environments remains limited. Additionally, most prior research targets traditional media such as television andmagazines, with fewer studies focusing on new media platforms like YouTube. Therefore, this study
simplifies the experimental environment by using
content tones (positive or negative) and includes
video streaming services to elucidate factors influencing media viewing preferences.

1. INTRODUCTION
In this study, we identify the factors influencing
viewing preferences for television and video streaming services (e.g., YouTube) among Japanese university students through experimental methods. Specifically, we presented participants with fictitious program content, providing them with pre-announcement texts of around 100 to 200 characters, and experimentally assessed their viewing preferences.
These announcements consisted of two components:
the medium of broadcast, the content tone of the program, and reference information about the host. We
statistically analyzed how combinations of positive
and negative attributes in these components affectedviewing preferences.
Previous research has extensively explored factors
influencing viewing preferences, primarily focusing
on television programs. For instance, Kwon et al.1)
conducted an integrated analysis of media contexts,
performing a meta-analysis of 70 studies on advertising messages to reveal content factors affecting advertisement recall. Similarly, van Reijmersdal et al.2)
investigated the relationship between context andconsumer behavior based on the theory of spillover
effects, surveying over 1,000 participants. However,these studies are often applied to marketing contexts,

Furthermore, many existing studies do not consider the impact of reference information on viewing
preferences. Reference information, which pertains
to the essence of the content, includes details about
hosts, participants, ratings, and program reputation.
While it is believed that such information affects
viewing preferences in media analysis practice, there
are few studies that have clarified this relationship.
Thus, this study also aims to reveal the impact of reference information on viewing preferences.
Another factor affecting viewing preferences is therespondent's attributes. For instance, Redfern3)'s research in the UK identified the relationship between
gender, age, and preferred program genres. Given1

General Academic Paper (refereed paper)that gender is recognized as a significant factor influencing human behavior across various fields such aspsychology, this study will focus on gender as a fundamental variable. Additionally, by targeting university students, who typically have higher media consumption, we aim to derive more specific results.
In summary, the characteristics of this study arethreefold. First, it uses an experimental environment
to clarify the impact of content tone on viewing preferences. Second, it investigates the influence of reference information on viewing preferences. Third, it
examines how the attributes of experimental participants, specifically gender, affect viewing preferences.
The remainder of the paper is organized as follows:
The experiment design is presented in Section 2, theanalysis results in Section 3, and the conclusion anddiscussion in Section 4.

3. MAIN RESULTS OF ANALYSISa) Differences in Viewing Preferences by Media
Platform
First, we aim to clarify whether there are differencesin viewing preferences by media platform, which previous research has not yet identified. Specifically, wecalculated the viewing preference scores (rangingfrom 1 to 5) for each participant separately by platform, based on the descriptions presented in Chapter
2. Each participant rated two descriptions for a given
platform (positive and negative content tones), resulting in a total viewing preference score ranging from
2 to 10 points per platform. At this stage, we did not
categorize participants by reference information orgender, as we will explore these factors in subsequent
analyses.
Figure 2 presents a comparison of the mean total
viewing preference scores. Hypothesis testing revealed no significant differences between platforms(for positive content tone: t(137) = 0.923, p = 0.358;
for negative content tone: t(137) = -0.717, p = 0.475).
In other words, within the scope of this study's analysis of program descriptions, we did not observe any
differences in viewing preferences based on the media platform. Therefore, in the following analyses, wewill proceed without considering platform differences.

2. EXPERIMENT DESIGN
We conducted the experiment from July to August
2023, targeting undergraduate students at a private
university in Japan, and recruited 138 participants on
a voluntary basis. we presented participants with several promotional descriptions of fictional talk show
and asked them to rate their viewing preferences using a 5-point Likert scale.
The descriptions varied by the platform on which
the program would be broadcast (television orYouTube), the tone of the content (positive or negative), and the type of reference information provided(positive, negative, or none). An illustration of thedescriptions is shown in a figure 1,2.
In the experimental procedure, we randomly assigned participants to one of three groups based on
the reference information: a group exposed to positive reference information, a group exposed to negative reference information, and a group not provided
with any reference information. Each participant,based on their assigned group, was presented withfour descriptions, created by crossing the two platforms and two content tones. Thus, each participant
viewed four descriptions and rated their viewing
preferences for each one.
Additionally, we collected demographic information from the participants. Specifically, we asked
them to provide their gender (male or female) andtheir average daily television viewing time on weekdays (none, less than 30 minutes, 30 minutes to 1hour, 1 to 2 hours, 2 to 3 hours, or more than 3 hours).
We then conducted statistical analyses of the participants' responses to determine how content tone andreference information influenced viewing preferences. The main findings are presented in the following section.

b) Factors Influencing Viewing Preferences
In this section, we identify factors that influenceviewing preferences using analysis of variance(ANOVA). Specifically, we conducted a three-way
ANOVA for each content tone (positive and negative), treating gender (2 categories), reference information (3 categories), and average television viewing
time on weekdays (6 categories) as the main effects,
and total viewing preference scores as the dependent
variable. Table 1 presents the ANOVA results for
positive content tone, while Table 2 shows the results
for negative content tone.
First, examining the positive content tone results(Table 1), we found a significant interaction between
the main effects of television viewing time and reference information. We then conducted simple main effects tests and multiple comparisons to identify theconditions under which significant differences occurred. As a result, we found that significant differences were present only between the "no reference
information" and "positive reference information"
conditions for participants who watched television
for 1 to 2 hours on average (Figure 3). Consideringthat the 1 to 2-hour category is the longest viewing
time for which all reference information conditions
were obtained within this experiment, we concluded
that participants who watch more television tend toincrease their viewing preferences only when the2General Academic Paper (refereed paper)
content tone and reference information align in a positive direction.
A new TV show, “Edo-chan Comedy TV“, will start airing
next month.

Platform(TV/YouTube)

Tone of the content(Positive/Negative)

Referenceinformation(Positive/Negative/None)

This variety comedy program stars Edo-chan, a rising
young comedian who has recently gained popularity. Theshow features 10-minute comedy skits, 1-minute shortskits, and occasional special segments such as travel
reports, making it an entertaining program.
Edo-chan frequently appears on other shows anddramas, and he ranked first in this year’s “Young
Comedian Rankings”. He is often a topic of conversation
among friends.
Would you like to watch this show?

Fig.1 Overview of Promotional Description (Positive tone of content and positive reference information condition)
A new YouTube channel, "Sai-san's Celebrity Exposé
Channel", will launch next month.

Platform(TV/YouTube)

Tone of the content(Positive/Negative)

Reference
information(Positive/Negative/None)

This channel features veteran entertainment reporter Saisan, who shares gossip, private information such ascelebrity marriages and divorces, and even scandals in theentertainment industry, making it a somewhat provocativechannel.
However, Sai-san's reports are often so sensational thatthey have led to defamation lawsuits from the celebrities
involved and online backlash (receiving criticism from many
viewers on social media). Sai-san's reports are also
considered controversial in conversations with friends.
Would you like to watch this channel?

Fig.2 Overview of Promotional Description (Negative tone of content and negative reference information condition)
Table 2. The Analysis Results of the Three-way ANOVA(Negative content tone)

Table 1. The Analysis Results of the Three-way ANOVA(Positive content tone)
Sum SqDfF value

Pr(>F)

Gender

0.24

10.0300.863

TV viewing time

59.7

51.5190.190

Reference info.

5.51

20.3500.705

Gender*TV viewing time
Gender*Reference info.
TV Viewing
time*Reference
info.
Gender*TV viewing time*Reference info.
Residuals

19.88
25.19

420.632
1.603

0.641
0.206

144.5382.299

0.026

66.79

71.2140.301

848.73108

Sum SqDfF value

Pr(>F)

Gender

3.26

10.381

0.539

TV viewing time

95.38

52.224

0.057

Reference info.

14.12

20.8230.442

Gender*TV viewing time

53.34

41.555

0.192

Gender*Reference info.

5.39

20.3140.731

120.8581.761

0.093

80.36

71.339

0.239

926.2

108

TV Viewing
time*Referenceinfo.
Gender*TV viewing time*Reference info.

*

3Residuals††

General Academic Paper (refereed paper)*

12.00010.000
8.000
6.000

4.000
2.000
0.000
No Ref.
Info.

Negative Positive
Ref. Info. Ref. Info.
None

No Ref.
Info.

Negative Positive
Ref. Info. Ref. Info.

No Ref.
Info.

Less than 30 minitutes

Negative Positive
Ref. Info. Ref. Info.

No Ref.
Info.

30 minutes to 1 hour

Negative Positive
Ref. Info. Ref. Info.
1 to 2 hours

No Ref.
Info.

Negative
Ref. Info.

2 to 3 hours

Fig. 3 Differences in Viewing Preferences by Main Effects Testing and Multiple Comparisons (Positive ContentTone)
Note 1: Responses for the 2-3 hour category under the positive reference information condition were not obtained
and therefore are excluded.
Note 2: The 3-hour or more category is excluded due to the lack of responses from at least two participants percondition.
Note 3:** * denotes p<0.05.
12.00010.000

*

8.000
6.000
4.000
2.000
0.000

No
Nnegative Positive
No
Nnegative Positive
No
Nnegative Positive
No
Nnegative Positive
nonegative
Additional Info.
Info. Additional Info.
Info. Additional Info.
Info. Additional Info.
Info. additional info.
Info.
Info.
Info.
Info.
info.
None

Less than 30 minitutes

30 minutes to 1 hour

1 to 2 hours

2 to 3 hours

Fig. 4 Differences in Viewing Preferences by Main Effects Testing and Multiple Comparisons (Negative Content Tone)

viewing preferences for negative content only when
the content tone and reference information align negatively. It is important to note that adding negativereference information to negative content essentially"exaggerates" the overall negativity of the description. While it might be expected that participants(viewers) would reduce their viewing preferences under such conditions, our results indicate an increasein viewing preferences, which suggests a unique effect.
On the other hand, for participants with shorter television viewing times, we found no significant differences across any conditions, regardless of content

Similarly, when analyzing the negative content tone
results (Table 2), we found a significant trend in theinteraction between television viewing time and reference information. As with the positive content tone,
we conducted simple main effects tests and multiple
comparisons, which revealed significant differences
only between the "no reference information" and"negative reference information" conditions for participants who watched television for 1 to 2 hours on
average (Figure 4). In other words, similar to the positive content tone, we concluded that participants
who watch more television tend to increase their4

General Academic Paper (refereed paper)
tone. Additionally, no significant differences wereobserved when the content tone and reference information did not align. Based on these results, we concluded that reference information only influences
viewing preferences for participants with longer
viewing times when the provided information aligns
with the content tone, and under these conditions,viewing preferences consistently improved.
Furthermore, within the scope of this study, we did
not observe any gender effects, which were highlighted in previous research, under any conditions.
We discuss this finding, along with other results, inthe next chapter.

public relations, practices such as "crisis management" and "crisis response" often aim to address negative media coverage, such as product recalls or political scandals, by continuously providing reference
information to shift public opinion positively. However, our results indicate that it is the combination ofnegative content tone with negative reference information that improves viewing preferences, rather
than the combination of negative content with positive reference information (such as product improvements or favorable information about politicians). In
other words, the effectiveness of information dissemination in crisis management, as traditionally conceived, is not supported by the findings of this study.
This result is of significant interest not only to experts
in public relations and media studies but also to practitioners in the field.
Finally, we outline future challenges. Firstly, future
research should diversify experimental conditions.
This study has so far highlighted specific program
genres and participant age groups, but researchers
should also consider varying the information delivery
methods, such as switching from presenting program
announcements to viewing advertising videos. Another important aspect is to examine in greater detailthe factors that improve viewing preferences for negative content. As previously discussed, methodologies to positively shape public opinion during instances of negative content are crucial in crisis management. Given that these methodologies are actively
debated in risk communication within social advancement, leveraging these findings to derive morepractical insights will be essential.

4. CONCLUSION AND DISCUSSION
In this study, we investigated the factors influencing
viewing preferences among Japanese university students through experimental methods. We identified
three main findings.
Firstly, reference information has a conditional impact on viewing preferences. It only affects the preferences of participants who watch television for
longer periods when it aligns with the content tone,
whether positive or negative. This finding refines andextends previous research on the impact of content
tone on viewing preferences, as highlighted by van
Reijmersdal et al.2) and Kwon et al.1) However, ourexperiment focused exclusively on the talk show
genre and did not explore the effect of information
value across multiple genres, as seen in van
Reijmersdal et al.2)’s research. Future studies should
consider different program genres and diverse conditions to discover more generalizable patterns in viewing preferences.
Secondly, we established that differences in media
platforms do not affect viewing preferences. This result addresses a condition not considered in previous
studies, such as those cited by Kwon et al. 1), and introduces new findings to the field of media viewing
preferences research. However, as mentioned earlier,
our study focused on a specific program genre, sothese results may be limited. Future research should
include additional experiments across a wider rangeof program genres to validate and expand upon thesefindings.
Thirdly, we clarified that no gender effects were observed under any of the conditions in our experiment.
This finding contrasts with Redfern3)'s study, whichinvestigated respondents in the UK and found gendereffects. However, Redfern's research included multiple program genres and a diverse age range, while ourstudy focused on a more specific set of conditions.
Thus, our results remain more limited in scope.
Among the findings of this study, the relationshipbetween content tone and reference information isparticularly interesting. For instance, in the field ofREFERENCES
[1]

[2]

[3]

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van Reijmersdal, E., Smit, E. and Neijens, P., How media
factors affect audience responses to brand placement, International Journal of Advertising, 29(2), 279-301, 2010.
Redfern, N., Age, gender and television in the United
Kingdom, Journal of Popular Television, 3(1), 57-73,2015.