Broadcast Media Questionnaires
Group2
2025-12-12
IMPACT OF DIGITAL TECHNOLOGY ON NEWS EDITING IN BROADCAST MEDIA
Statement of the Problem
The integration of digital technology has introduced unprecedented media freedom in information dissemination. However, these changes are already having significant implications for media operations due to evolving modes of media production and consumption. Unfortunately, digital technology has also enabled the widespread use of hate speech. According to Uche and Ukweze (2015), the media has been used to amplify hateful rhetoric, often reaching larger audiences than ever before. The United Nations defines hate speech as “any advocacy of national, racial, or religious hatred that constitutes incitement to discrimination, hostility or violence.” This study seeks to explore the impact of digital technology on news editing in broadcast media, assessing both its benefits and downsides. It aims to analyze how digital tools affect the accuracy, authenticity, and credibility of news content.
Research Questions
This study seeks to answer the following questions:
How has digital technology transformed the news editing process in broadcast media?
What challenges do broadcast media organizations face in adopting digital technology for news editing?
What are the advantages of using digital tools in news editing compared to traditional methods?
How has digital technology impacted the speed and efficiency of news production in broadcast media?
Loading Necessary Libraries
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#importing data set
broadcast<-read.csv("~/GLADYS FOLDER .R/IMPACT OF DIGITAL TECHNOLOGY ON NEWS EDITING IN BROADCAST MEDIA (Responses) - Form Responses 1.csv")
#View(broadcast)
dim(broadcast)## [1] 90 30unique(broadcast$Age)## [1] "20-29 years" "40-49 years" "Less than 20 years"
## [4] "50 years and above" "30-39 years"#is.na(broadcast)
summary(broadcast)## Timestamp Gender Age
## Length:90 Length:90 Length:90
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
## What.is.your.primary.job.role.
## Length:90
## Class :character
## Mode :character
## How.many.years.of.experience.do.you.have.in.broadcast.media.
## Length:90
## Class :character
## Mode :character
## What.is.your.highest.educational.qualification.
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.digital.technology.has.radically.changed.the.daily.operations.related.to.news.editing..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...My.work.duties.have.expanded.to.include.a.wider.scope.of.activities.such.as.graphic.design..audio.production..and.social.media.management.than.was.customarily.the.case..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.cloud.based.infrastructures.have.significantly.transformed.the.way.I.work.with.reporters.and.producers..especially.when.dealing.with.remote.situations..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...What.used.to.be.considered.a.luxury.item.in.my.editorial.workflows..e.g..automated.transcription.services.or.clip.generation.algorithms.powered.by.artificial.intelligence..is.becoming.a.commonplace.feature..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.fact.that.there.is.now.an.influence.by.audience.analytics.and.real.time.social.media.feedback.on.my.editorial.decision.making..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.technology.has.changed.my.attention.to.editing.to.suit.one.broadcast.channel.to.suit.the.various.platforms..such.as.web.and.social.media.platforms..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.huge.cost.encircling.the.purchase.and.upgrading.of.digital.software.and.hardware.is.a.major.organisational.issue..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...My.organisation.has.not.been.offering.adequate.training.to.enable.the.learning.of.the.new.digital.editing.tools..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.urgency.to.release.news.as.fast.as.possible.in.the.digital.age.increases.the.chances.of.spreading.inaccuracies.in.facts..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...There.is.a.significant.challenge.of.ensuring.the.authenticity.of.digital.content..including.deep.fakes.or.manipulated.videos..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...My.concern.is.the.cybersecurity.stance.of.our.online.newsroom..including.such.threats.as.hacking.and.data.leaks..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...I.fear.that.the.digital.technology..especially.artificial.intelligence..can.threaten.my.long.term.job.security..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.editing.software..such.as.non.linear.editors..allow.me.more.creative.freedom.and.ability.to.manipulate.than.traditional.techniques..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.digital.systems.make.retrieval.and.utilisation.of.the.archival.footage.and.other.ancillary.materials.easier..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.technical.quality.of.our.end.product.of.the.news..including.audio.fidelity.and.video.resolution..has.also.been.significantly.enhanced.with.the.use.of.digital.tools..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.tools.enable.it.to.be.easy.to.incorporate.content.provided.by.various.sources..including.social.media.and.citizen.journalists.and.tie.them.together.into.a.unified.reporting..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.technology.offers.better.ways.of.rectifying.mistakes.or.changing.stories.after.they.have.been.aired..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Online.technologies.allow.me.to.create.and.edit.high.quality.news.products.when.being.at.a.distance..be.it.in.the.field.or.at.home..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.technology.allows.me.to.edit.news.materials.at.a.much.faster.rate..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Online.applications.have.increased.the.productivity.of.my.personal.life.and.the.amount.of.work.that.I.am.able.to.accomplish.in.an.average.day..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...The.entire.news.making.process.of.my.organisation..namely.field.collection.to.broadcast..is.more.efficient.due.to.the.digital.technology..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Automated.utilities.e.g..spell.checkers.and.transcribers.have.cut.down.the.amount.of.time.spent.on.manual.and.routine.activities..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.technology.enables.us.to.make.news.and.broadcast.reports.with.minimum.latency..
## Length:90
## Class :character
## Mode :character
## Please.indicate.your.level.of.agreement.with.the.following.statements.based.on.your.professional.experience...Digital.workflows.also.allow.simultaneous.performance.of.tasks..such.as.editing.when.the.footage.is.still.being.shot..thus..increasing.the.general.speed.of.operation..
## Length:90
## Class :character
## Mode :characterRenaming Column Name
new_column_names <- c(
"Timestamp", "Gender", "Age", "Job_Role", "Years_Experience", "Education",
"Q01_Changed_Operations", "Q02_Duties_Expanded", "Q03_Cloud_Remote_Work",
"Q04_AI_Commonplace", "Q05_Audience_Analytics_Influence", "Q06_Editing_Multiplatform",
"Q07_Challenge_High_Cost", "Q08_Challenge_Inadequate_Training", "Q09_Challenge_Urgency_Inaccuracies",
"Q10_Challenge_Authenticity_Deepfakes", "Q11_Challenge_Cybersecurity", "Q12_Challenge_Job_Security_Fear",
"Q13_Advantage_Creative_Freedom", "Q14_Advantage_Easier_Archival", "Q15_Advantage_Enhanced_Quality",
"Q16_Advantage_Easier_UGC_Incorporation", "Q17_Advantage_Easier_Rectification", "Q18_Advantage_Remote_Editing",
"Q19_Efficiency_Faster_Editing", "Q20_Efficiency_Personal_Productivity", "Q21_Efficiency_Overall_Process",
"Q22_Efficiency_Automated_Utilities", "Q23_Efficiency_Minimum_Latency", "Q24_Efficiency_Simultaneous_Tasks"
)
colnames(broadcast) <- new_column_names
colnames(broadcast)## [1] "Timestamp"
## [2] "Gender"
## [3] "Age"
## [4] "Job_Role"
## [5] "Years_Experience"
## [6] "Education"
## [7] "Q01_Changed_Operations"
## [8] "Q02_Duties_Expanded"
## [9] "Q03_Cloud_Remote_Work"
## [10] "Q04_AI_Commonplace"
## [11] "Q05_Audience_Analytics_Influence"
## [12] "Q06_Editing_Multiplatform"
## [13] "Q07_Challenge_High_Cost"
## [14] "Q08_Challenge_Inadequate_Training"
## [15] "Q09_Challenge_Urgency_Inaccuracies"
## [16] "Q10_Challenge_Authenticity_Deepfakes"
## [17] "Q11_Challenge_Cybersecurity"
## [18] "Q12_Challenge_Job_Security_Fear"
## [19] "Q13_Advantage_Creative_Freedom"
## [20] "Q14_Advantage_Easier_Archival"
## [21] "Q15_Advantage_Enhanced_Quality"
## [22] "Q16_Advantage_Easier_UGC_Incorporation"
## [23] "Q17_Advantage_Easier_Rectification"
## [24] "Q18_Advantage_Remote_Editing"
## [25] "Q19_Efficiency_Faster_Editing"
## [26] "Q20_Efficiency_Personal_Productivity"
## [27] "Q21_Efficiency_Overall_Process"
## [28] "Q22_Efficiency_Automated_Utilities"
## [29] "Q23_Efficiency_Minimum_Latency"
## [30] "Q24_Efficiency_Simultaneous_Tasks"unique(broadcast$Age)## [1] "20-29 years" "40-49 years" "Less than 20 years"
## [4] "50 years and above" "30-39 years"Standardization of age
broadcast <- broadcast %>%
mutate(
# Create a new, clean Age category
Age_Standardized = case_when(
Age == "Less than 20 years" ~ "< 20",
Age == "20-29 years" ~ "20-29",
Age == "30-39 years" ~ "30-39",
Age == "40-49 years" ~ "40-49",
Age == "50 years and above" ~ "50+",
TRUE ~ Age # Keeps any other unexpected value (though none are expected)
)
)
# Define the correct, ordered factor levels for plotting
age_levels_ordered <- c("< 20", "20-29", "30-39", "40-49", "50+")
# Apply the ordered factor levels
broadcast$Age_Standardized <- factor(broadcast$Age_Standardized, levels = age_levels_ordered)What the code did:
It created a new column called Age_Standardized
It replaced long age labels with shorter, cleaner ones
Converting categorical variable to factor
categorical_cols <- c(
"Gender", "Age_Standardized", "Job_Role",
"Years_Experience", "Education"
)
broadcast[categorical_cols] <- lapply(broadcast[categorical_cols], as.factor)# converting all likert variables to factors
likert_cols <- c(
"Q01_Changed_Operations",
"Q02_Duties_Expanded",
"Q03_Cloud_Remote_Work",
"Q04_AI_Commonplace",
"Q05_Audience_Analytics_Influence",
"Q06_Editing_Multiplatform",
"Q07_Challenge_High_Cost",
"Q08_Challenge_Inadequate_Training",
"Q09_Challenge_Urgency_Inaccuracies",
"Q10_Challenge_Authenticity_Deepfakes",
"Q11_Challenge_Cybersecurity",
"Q12_Challenge_Job_Security_Fear",
"Q13_Advantage_Creative_Freedom",
"Q14_Advantage_Easier_Archival",
"Q15_Advantage_Enhanced_Quality",
"Q16_Advantage_Easier_UGC_Incorporation",
"Q17_Advantage_Easier_Rectification",
"Q18_Advantage_Remote_Editing",
"Q19_Efficiency_Faster_Editing",
"Q20_Efficiency_Personal_Productivity",
"Q21_Efficiency_Overall_Process",
"Q22_Efficiency_Automated_Utilities",
"Q23_Efficiency_Minimum_Latency",
"Q24_Efficiency_Simultaneous_Tasks"
)
broadcast[likert_cols] <- lapply(broadcast[likert_cols], as.factor)
# Check exactly how your Likert responses appear
sort(unique(unlist(broadcast[likert_cols])))## [1] Agree Disagree Strongly Agree Strongly Disagree
## [5] Neutral
## Levels: Agree Disagree Strongly Agree Strongly Disagree NeutralRECODE LIKERT RESPONSES TO NUMERIC
The Likert scale is a rating scale used in surveys to measure people’s opinions, attitudes, or perceptions.whereby each response represents level of agreement.
likert_scale <- c(
"Strongly Disagree" = 1,
"Disagree" = 2,
"Neutral" = 3,
"Agree" = 4,
"Strongly Agree" = 5
)
# Convert each Likert column to numeric scale
news_numeric <- broadcast
news_numeric[likert_cols] <- lapply(news_numeric[likert_cols], function(x) {
as.numeric(recode(x, !!!likert_scale))
})We converted the text responses to numeric to enable us calculate averages and patterns.
Pivot longer for better visualization
news_long <- broadcast %>%
pivot_longer(
cols = all_of(likert_cols),
names_to = "Question",
values_to = "Response"
)
news_long$ResponseNum <- as.numeric(recode(news_long$Response, !!!likert_scale))We did this for better visualizations
Bivariate Analysis
This shows whether perceptions of digital tools differ across roles
news_long$Theme <- case_when(
news_long$Question %in% c("Q01_Changed_Operations","Q02_Duties_Expanded","Q03_Cloud_Remote_Work","Q04_AI_Commonplace",
"Q05_Audience_Analytics_Influence",
"Q06_Editing_Multiplatform") ~ "Transformation",
news_long$Question %in% c("Q07_Challenge_High_Cost",
"Q08_Challenge_Inadequate_Training",
"Q09_Challenge_Urgency_Inaccuracies",
"Q10_Challenge_Authenticity_Deepfakes",
"Q11_Challenge_Cybersecurity",
"Q12_Challenge_Job_Security_Fear") ~ "Challanges",
news_long$Question %in% c("Q13_Advantage_Creative_Freedom",
"Q14_Advantage_Easier_Archival",
"Q15_Advantage_Enhanced_Quality",
"Q16_Advantage_Easier_UGC_Incorporation",
"Q17_Advantage_Easier_Rectification",
"Q18_Advantage_Remote_Editing") ~ "Advantages",
news_long$Question %in% c("Q19_Efficiency_Faster_Editing",
"Q20_Efficiency_Personal_Productivity",
"Q21_Efficiency_Overall_Process",
"Q22_Efficiency_Automated_Utilities",
"Q23_Efficiency_Minimum_Latency",
"Q24_Efficiency_Simultaneous_Tasks") ~ "Speed $ Efficacy",
TRUE ~ "Other"
)plot
ggplot(news_long, aes(x = Job_Role, fill = factor(Response))) +
geom_bar(position = "dodge") +
facet_wrap(~Theme) + # separate plots per research question theme
scale_fill_manual(values = c("#FF6F61", "#6B5B99", "#88B04B", "#F7C", "#92A8D5"),
name = "Likert Score")+
#coord_flip()+
labs(
title = "Responses by Job Role Across Research Question Themes",
x = "Job Role",
y = "Count of Responses"
) +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 45, hjust = 1),
plot.title = element_text(hjust = 0.5, face = "bold")
)
The analysis of mean response scores by Job Role reveals key differences in how broadcast professionals perceive digital technology across the study’s themes. Overall, there is strong consensus on Transformation (RQ(i)), with all roles agreeing that the industry has changed, particularly Reporters (3.48). However, opinions diverge on challenges and benefits: while all roles are generally skeptical about the severity of Challenges (RQ(ii)) and the realization of Advantages (RQ(iii))—with scores near or below the neutral 3.0 line—Reporters (2.85) show the greatest level of concern for the challenges. Crucially, the theme of Efficiency (RQ(iv)) received the lowest average scores across the board, highlighting widespread disappointment with digital workflows, especially among Producers (2.44), who registered the strongest average disagreement regarding improvements in speed and personal productivity.
ANALYSIS FOR EACH RESEARCH QUESTION
RQ1: How has digital technology transformed the news editing process in broadcast media?
Summary statistics
RQ1_questions <- likert_cols[1:6]
RQ1_summary <- news_numeric %>%
summarise(across(all_of(RQ1_questions), mean, na.rm = TRUE)) %>%
pivot_longer(cols = everything(),
names_to = "Question",
values_to = "Mean_Score")## Warning: There was 1 warning in `summarise()`.
## ℹ In argument: `across(all_of(RQ1_questions), mean, na.rm = TRUE)`.
## Caused by warning:
## ! The `...` argument of `across()` is deprecated as of dplyr 1.1.0.
## Supply arguments directly to `.fns` through an anonymous function instead.
##
## # Previously
## across(a:b, mean, na.rm = TRUE)
##
## # Now
## across(a:b, \(x) mean(x, na.rm = TRUE))print(RQ1_summary)## # A tibble: 6 × 2
## Question Mean_Score
## <chr> <dbl>
## 1 Q01_Changed_Operations 2.81
## 2 Q02_Duties_Expanded 3.23
## 3 Q03_Cloud_Remote_Work 2.9
## 4 Q04_AI_Commonplace 2.88
## 5 Q05_Audience_Analytics_Influence 3.2
## 6 Q06_Editing_Multiplatform 2.66Q01 – News Operations Have Changed (2.81)
This is closer to agree which means that respondents somewhat agree that digital technology has changed how newsrooms operate—workflow is faster, more integrated, and less manual.
Q02 – Duties Have Expanded (3.23)
This is the highest score, showing a strong shift: Editors now multitask across writing, editing, publishing, and social media platforms.
Q03 – Remote/Cloud-Based Work (2.90)
Slightly above agree → meaning digital tools now allow editing from anywhere (remote/cloud systems).
Q04 – AI Becomes Common (2.88)
Editors recognize that AI features (auto-captioning, transcription, auto-editing) are emerging in their workflow.
Q05 – Audience Influence on Editing (3.20)
Digital analytics strongly impact decisions—this is a major transformation in modern editing.
Q06 – Multi platform Editing (2.66)
Editors agree that they now edit for multiple platforms (TV, YouTube, social media).
Prepare data for plotting
RQ1_data <- news_long %>%
filter(Question %in% RQ1_questions) %>%
mutate(Response = factor(ResponseNum,
levels = c(1, 2, 3, 4,5),
labels = c("Strongly Disagree", "Disagree", "Neutral",
"Agree", "Strongly Agree")))Plot
ggplot(RQ1_data, aes(x = ResponseNum)) +
geom_bar(fill = "steelblue") +
facet_wrap(~Question) +
labs(title = "RQ1: Transformation of News Editing by Digital Technology",
x = "Response", y = "Count") +
coord_flip() +
theme_bw()
The distribution shows some mixed responses, suggesting that while change is happening, it is not uniformly experienced across all staff. The plot for duties expanded shows that a large part of the responses strongly agree. Hence, we can say that editors feel digital tools have increased or expanded their responsibilities, allowing them to do more tasks like scripting, video editing, social media preparation, etc.
The plot for Q5 (Audience Analytics) also shows that editors also agree that they consider audience engagement and social feedback when editing or selecting news stories.
RQ2: What challenges do broadcast media organizations face in adopting digital technology for news editing?
Summary statistics
RQ2_questions <- likert_cols[7:12]
RQ2_summary <- news_numeric %>%
summarise(across(all_of(RQ2_questions), mean, na.rm = TRUE)) %>%
pivot_longer(cols = everything(),
names_to = "Question",
values_to = "Mean_Score")
print(RQ2_summary)## # A tibble: 6 × 2
## Question Mean_Score
## <chr> <dbl>
## 1 Q07_Challenge_High_Cost 3.27
## 2 Q08_Challenge_Inadequate_Training 3.09
## 3 Q09_Challenge_Urgency_Inaccuracies 3.14
## 4 Q10_Challenge_Authenticity_Deepfakes 3.13
## 5 Q11_Challenge_Cybersecurity 3.09
## 6 Q12_Challenge_Job_Security_Fear 3.04The mean score is saying that:
Q07_Challenge_High_Cost:
Respondents indicate that the high cost of digital technology is a significant challenge in adopting new tools in news editing.
Q08_Challenge_Inadequate_Training:
Lack of proper training is perceived as a moderate challenge for editors when using digital technology.
Q09_Challenge_Urgency_Inaccuracies:
The pressure to produce news quickly, sometimes leading to inaccuracies, is a notable concern among respondents.
Q10_Challenge_Authenticity_Deepfakes:
Deepfakes and false information, are concerns in maintaining authenticity in digital news content.
Q11_Challenge_Cybersecurity:
Respondents consider cybersecurity threats—such as hacking or data breaches—as a moderate challenge in adopting digital technology.
Q12_Challenge_Job_Security_Fear:
Indicating that fear of job loss due to automation or digital tools is a smaller, though still present, concern among news editors
Prepare data for plotting
RQ2_data <- news_long %>%
filter(Question %in% RQ2_questions) %>%
mutate(Response = factor(ResponseNum,
levels = c(1, 2, 3, 4),
labels = c("Strongly Disagree", "Disagree",
"Agree", "Strongly Agree")))Plot
ggplot(RQ2_data, aes(x = ResponseNum)) +
geom_bar(fill = "tomato") +
facet_wrap(~Question) +
labs(title = "RQ2: Challenges in Digital Technology Adoption (Q07–Q12)",
x = "Response", y = "Count") +
coord_flip() +
theme_bw()
The plot for Q07–Q12 indicate several challenges in adopting digital technology in news editing. High costs are seen as the most significant barrier, followed closely by concerns about inaccuracies under tight deadlines and issues with authenticity, including deepfakes . Inadequate training and cybersecurity threats are also moderate concerns for respondents. Fear of job insecurity due to digital tools is the least pronounced challenge but remains a consideration. Overall, the data suggests that while technology adoption offers clear benefits, financial, skill-related, and ethical challenges continue to influence its implementation in broadcast media.
RQ3: What are the advantages of using digital tools in news editing compared to traditional methods?
Summary statistics
RQ3_questions <- likert_cols[13:18]
RQ3_summary <- news_numeric %>%
summarise(across(all_of(RQ3_questions), mean, na.rm = TRUE)) %>%
pivot_longer(cols = everything(),
names_to = "Question",
values_to = "Mean_Score")
print(RQ3_summary)## # A tibble: 6 × 2
## Question Mean_Score
## <chr> <dbl>
## 1 Q13_Advantage_Creative_Freedom 3.09
## 2 Q14_Advantage_Easier_Archival 3.01
## 3 Q15_Advantage_Enhanced_Quality 3.22
## 4 Q16_Advantage_Easier_UGC_Incorporation 2.82
## 5 Q17_Advantage_Easier_Rectification 2.89
## 6 Q18_Advantage_Remote_Editing 2.93Q13_Advantage_Creative_Freedom : The mean score indicate that digital tools allow editors more creative freedom, such as experimenting with multimedia formats or interactive storytelling.
Q14_Advantage_Easier_Archival : Respondents generally agree that digital tools make archiving and retrieving past content easier, which in real life means faster access to past news clips or documents when preparing reports or follow-ups.
Q15_Advantage_Enhanced_Quality : The mean score suggest that digital tools noticeably improve content quality—better video/audio editing, sharper visuals, and polished graphics for broadcast.
Q16_Advantage_Easier_UGC_Incorporation : The mean score suggest that incorporating user-generated content (UGC) is somewhat less utilized. In practice, editors may find it challenging to verify or integrate audience-submitted videos or images quickly.
Q17_Advantage_Easier_Rectification :
Respondents moderately agree that mistakes can be corrected more easily with digital tools, such as fixing typos in online scripts or updating broadcast content promptly.
Q18_Advantage_Remote_Editing : The mean score suggest that digital tools support remote editing.
Prepare data for plotting
RQ3_data <- news_long %>%
filter(Question %in% RQ3_questions) %>%
mutate(Response = factor(ResponseNum,
levels = c(1, 2, 3, 4),
labels = c("Strongly Disagree", "Disagree",
"Agree", "Strongly Agree")))Plot
ggplot(RQ3_data, aes(x = ResponseNum)) +
geom_bar(fill = "green4") +
facet_wrap(~Question) +
labs(title = "RQ3: Advantages of Digital Tools",
x = "Response", y = "Count") +
coord_flip() +
theme_bw()
The plot highlight several key advantages of digital tools in news editing. Enhanced quality stands out as the most recognized benefit, reflecting real-life improvements in video, audio, and graphics production. Respondents also value creative freedom and easier archival of past content, which allow editors to experiment with storytelling and quickly retrieve previous reports. Remote editing and easier rectification of mistakes show that digital tools facilitate flexible workflows and quick corrections. Incorporating user-generated content is slightly less emphasized, suggesting that verifying and integrating audience submissions can still be challenging.
Overall, the data indicates that digital technology enhances productivity, quality, and flexibility in broadcast media, while some practical challenges remain in integrating audience contributions.
RQ4: How has digital technology impacted the speed and efficiency of news production in broadcast media?
Summary statistics
RQ4_questions <- likert_cols[19:24]
RQ4_summary <- news_numeric %>%
summarise(across(all_of(RQ4_questions), mean, na.rm = TRUE)) %>%
pivot_longer(cols = everything(),
names_to = "Question",
values_to = "Mean_Score")
print(RQ4_summary)## # A tibble: 6 × 2
## Question Mean_Score
## <chr> <dbl>
## 1 Q19_Efficiency_Faster_Editing 2.8
## 2 Q20_Efficiency_Personal_Productivity 2.72
## 3 Q21_Efficiency_Overall_Process 2.84
## 4 Q22_Efficiency_Automated_Utilities 2.83
## 5 Q23_Efficiency_Minimum_Latency 3.12
## 6 Q24_Efficiency_Simultaneous_Tasks 3.03Faster Editing (Q19): indicate that respondents slightly disagree that digital tools make editing faster.
Personal Productivity (Q20): suggests that individual productivity is not dependent on digital tools.
Overall Process Efficiency (Q21): shows a general perception that the editing process has become somewhat more efficient.
Automated Utilities (Q22): reflect disagreement that automation tools help streamline tasks.
Minimum Latency (Q23): indicate respondents are indifferent about digital tools being effective in reducing delays or wait times.
Simultaneous Tasks (Q24): suggests that respondents can multitask with or without digital tools
Prepare data for plotting
RQ4_data <- news_long %>%
filter(Question %in% RQ4_questions) %>%
mutate(Response = factor(ResponseNum,
levels = c(1, 2, 3, 4,5),
labels = c("Strongly Disagree", "Disagree","Neutral",
"Agree", "Strongly Agree")))Plot
ggplot(RQ4_data, aes(x = ResponseNum)) +
geom_bar(fill = "yellow3") +
facet_wrap(~Question) +
labs(title = "RQ4: Speed & Efficiency ",
x = "Response", y = "Count") +
coord_flip() +
theme_bw()
Based on the survey responses, digital technology appears to have had a mixed impact on the speed and efficiency of news production in broadcast media. Respondents slightly disagreed that digital tools make editing faster (Q19) and indicated that personal productivity does not necessarily depend on these tools (Q20). However, there is a perception that the overall editing process has become somewhat more efficient (Q21), even though automation tools are not widely seen as significantly streamlining tasks (Q22). Respondents were neutral regarding whether digital tools reduce delays or wait times (Q23), and they reported being able to manage multiple tasks with or without digital tools (Q24).
Overall, while digital technology has introduced some improvements in process efficiency, its impact on individual speed and productivity remains limited.
Conclusion
The analysis shows that digital technology has significantly transformed the news editing process in broadcast media.. Overall, digital editing systems have become essential for modern newsrooms, enabling faster production, higher-quality output, and smoother editorial coordination.