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index.Rmd
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---
title: "Analysis: How successful was LEAFF 2020?"
subtitle: "[London East Asia Film Festival (LEAFF)](https://www.leaff.org.uk/)"
author: "[Avision Ho](https://github.com/avisionh), Strategy"
date: "`r Sys.Date()`"
output:
tufte::tufte_html: default
tufte::tufte_book:
citation_package: natbib
latex_engine: xelatex
link-citations: yes
---
```{r setup, include = FALSE}
# For markdown template
library(tufte)
# Load relevant packages for project
library(readr)
library(dplyr)
library(stringr)
library(tidyselect)
library(ggplot2)
library(pander)
# invalidate cache when the tufte version changes
knitr::opts_chunk$set(tidy = FALSE, cache.extra = packageVersion('tufte'))
options(htmltools.dir.version = FALSE)
knitr::opts_chunk$set(results = "asis", warning = FALSE, message = FALSE)
# Load scripts and data
source("scripts/0 - functions.R")
data_survey <- read_csv(file = 'data/data_survey.csv')
# Turn off scientific notation
options(scipen = 999, expressions = 10000)
cb_palette <- c("cb_black" = "#000000",
"cb_grey" = "#999999",
"cb_orange" = "#E69F00",
"cb_light_blue" = "#56B4E9",
"cb_green" = "#009E73",
"cb_yellow" = "#F0E442",
"cb_dark_blue" = "#0072B2",
"cb_red" = "#D55E00",
"cb_pink" = "#CC79A7")
```
# Executive Summary
```{r (HIDE) Exec Summary (also in 1.1 Rating - text), echo = FALSE, include = FALSE}
source("scripts/2.1 - reportRating.R")
source("scripts/2.2 - reportRecommend.R")
source("scripts/2.3 - reportEthnicity.R")
source("scripts/2.4 - reportMotivation.R")
source("scripts/2.5 - reportRetention.R")
```
```{r Exec Summary - side-image, echo = FALSE, fig.margin = TRUE}
knitr::include_graphics('pictures/poster.jpg')
```
From the post-film survey data, the key findings drawn from those who have attended the festival and filled out a survey are:
**`r toString(paste0(txt_rating * 100, "%"))` rated their LEAFF experience to be "Very good" or "Good".**
**`r toString(paste0(txt_recommend * 100, "%"))` enjoyed LEAFF so much that they would recommend a friend or colleague to attend LEAFF.**
**Most of the audience were from an `r toString(txt_ethnicity)` ethnic background. This shows LEAFF is `r toString(txt_ethnicity_conc)` the attendance of ethnic minority groups.**
***`r toString(txt_motivation)`* were the top three reasons why they wanted to attend LEAFF.**
**`r toString(paste0(txt_retention_new * 100, "%"))` said this is their first time coming to the festival, showing that LEAFF was `r toString(txt_retention_stay[2])` in attracting new audience members and retaining previous members.**
***
# Introduction
```{r Intro - side-image, echo = FALSE, fig.margin = TRUE}
knitr::include_graphics('pictures/director.jpg')
```
> _The London East Asia Film Festival (LEAFF) is the largest film festival of its kind in London, and represents the culmination of the most inspiring, engaging and inclusive cross-cultural programming. During these turbulent times, it is crucial that we move to understand each other on a humanist and artistic plain, and the exhibition of film — through festivals such as ours — is vital in aiding that communication._
> _After a hugely popular fourth edition in 2019, we return for our fifth year. We at LEAFF believe that the importance of our festival lies in extending a hand across cultures through the dynamics of story-telling and cinema; and as a global hub, London represents the perfect Western gateway to show films from all over East Asia, appreciating the rich diversity of a region bubbling with creativity and renewal._
> _In a year where many of us have felt stuck, our festival will allow audiences to be transported to new places and vibrant environments. Therefore, rather than make this edition an online event, our festival will be held in physical theatres across London. We passionately believe this is the only way to move audiences in true and, much needed, cinematic style. It means so much to us that we can continue celebrating Asian culture and platforming important stories through LEAFF this year._
> _Just like our festival’s emblem, the fish, as a team, we are unblinking and forever moving forward, traversing new lands and stories through film. We welcome you to participate in this journey, and to our festival this year!_
>
> `r quote_footer('--- Hyejung Jeon, Festival Director')`
`r newthought('This paper analyses the data')` collected from the London East Asia Film Festival (LEAFF) 2020. It does so with the intention of providing a summary of how successful the event was, and to provide a benchmark for future editions
***
# Section 1: Quotes from the Audience
```{r Quotes - side-image-one, echo = FALSE, fig.margin = TRUE}
knitr::include_graphics('pictures/opening_gala.jpg')
```
```{r Quotes - side-image-two, echo = FALSE, fig.margin = TRUE}
knitr::include_graphics('pictures/closing_gala.jpg')
```
`r newthought("This section presents")` some of the comments made by audience members who have attended LEAFF 2020.
> _"...really gives the Asian community something to look forward to."_
> _"Thank you for holding the events at he difficult time!"_
> _"Thank you very much for a great evening."_
> _"EXCELLENT TOTALLY IMMERSIVE FILM"_
> _"...very pleased it was able to run."_
> _"This is my favourite festival."_
> _"Excellent venue and staff!"_
> _"Great festival!"_
> `r quote_footer('--- LEAFF 2020 audience members')`
***
# Section 2: Key Performance Metrics
`r newthought("This section presents")` key analyis of the festival's performance data.
## Section 2.1: How much did the audience enjoy LEAFF?
```{r (SHOW) 2.1 Rating - plot, echo = FALSE, fig.margin = TRUE, fig.cap = "Figure 1", fig.width = 5, fig.height = 4}
# Create levels so we capture all responses and in right order
lvls_factors <- c("Very good", "Good", "Average", "Poor", "Very poor")
lvls_int <- rev(seq(5))
data_rating <- data_rating %>%
# select only columns we need
select(question, selection) %>%
# force factor order
mutate(selection = factor(x = selection, levels = lvls_int, labels = lvls_factors))
# Plot the rating
func_plot_counts_percents(x = data_rating,
col_x = "selection",
colour_fill = cb_palette[["cb_green"]],
plot_title = "Rating of Experience",
plot_title_x = "How would you rate your experience of LEAFF 2020?")
```
+ In **Figure 1**, `r toString(paste0(txt_rating * 100, "%"))` of attendees rated their LEAFF experience as being **Very good** or **Good**.
+ This demonstrates that `r toString(txt_rating_conc[1])` attendees enjoyed LEAFF and that the programme and activities which were part of this were `r toString(txt_rating_conc[2])` in capturing the public's interests and appetite for film and cinema.
## Section 2.2: How likely are the audience to recommend LEAFF to friends and colleagues?
+ In the table below, `r toString(paste0(txt_recommend * 100, "%"))` of respondents said they were either **Very likely** or **Likely** to recommend a friend or colleague to attend LEAFF.
+ This `r toString(txt_recommend_conc)` the findings made in *Section 2.1* where `r toString(paste0(txt_rating * 100, "%"))` of respondents said their experience of LEAFF was **Very good** or **Good**.
```{r (SHOW) 2.2 Recommend - table, echo = FALSE, fig.margin = TRUE}
table_future <- table_future %>%
mutate(selection = case_when(selection == 1 ~ "Very unlikely",
selection == 2 ~ "Unlikely",
selection == 3 ~ "Neurtal",
selection == 4 ~ "Likely",
selection == 5 ~ "Very likely")) %>%
rename("Response" = "selection",
"Count" = "n")
pander(x = table_future,
caption = "_Likelihood of audience recommending LEAFF to friends or colleagues_")
```
## Section 2.3: Is LEAFF appealing to minority ethnic groups in London?
```{r (SHOW) 2.3 No. ofscreenings - plot, echo = FALSE, fig.margin = TRUE, fig.cap = "Figure 2: Only showing groups with higher than 10%", fig.width = 5, fig.height = 7}
filter_ethnicity <- data_ethnicity %>%
group_by(selection) %>%
tally() %>%
mutate(Percent = round(x = n/sum(n), digits = 2)) %>%
filter(Percent > 0.1) %>%
select(selection) %>%
pull()
func_plot_counts_percents(x = filter(.data = data_ethnicity, selection %in% filter_ethnicity),
col_x = "selection",
colour_fill = cb_palette["cb_dark_blue"],
plot_title = "Audience Ethnicity",
plot_title_x = "What is your ethnicity?") +
coord_flip()
```
+ In **Figure 2**, the majority of the audience who attended LEAFF and completed the survey are of the **`r toString(txt_ethnicity)`** ethnic group.
+ This shows LEAFF is `r toString(txt_ethnicity_conc)` the attendance of ethnic minority groups to watch film.
## Section 2.4: Why does our audience come to LEAFF?
+ Digging further into why `r toString(paste0(txt_rating * 100, "%"))` of survey respondents enjoyed their LEAFF experience to rate it as **Very good** or **Good**, we see the top three reasons for why they wanted to attend LEAFF were *`r toString(txt_motivation)`*.
+ This demonstrates that LEAFF is more than just a festival but provides immense cultural value in broadening people's horizons.
## Section 2.5: How many previous and new audiences came to LEAFF?
```{r (SHOW) 2.5 Retention - plot, echo = FALSE, fig.margin = TRUE, fig.cap = "Figure 3", fig.width = 7, fig.height = 7}
lvls <- c("No, this is my first!", "Yes")
func_plot_pie(x = table_retention, col_counts = "Percent", col_category = "Selection_New",
plot_title = "Audience Retention", factor_levels = lvls)
```
+ In **Figure 3**, we have `r toString(paste0(txt_retention_new * 100, "%"))` of respondents saying this is their first time coming to the festival.
+ Of the remaining `r toString(paste0((1 - txt_retention_new) * 100, "%"))` of respondents who have returned from previous festivals, we have the following breakdown:
- `r toString(txt_retention[1])`
- `r toString(txt_retention[2])`
- `r toString(txt_retention[3])`
- `r toString(txt_retention[4])`
- `r toString(txt_retention[5])`
+ As a `r toString(txt_retention_stay[1])` proportion of attendees have returned to LEAFF from previous years, then this demonstrates that previous LEAFFs were `r toString(txt_retention_stay[2])` in encouraging people to return for this year's festival.
***
# Concluding Remarks
```{r Conclusion - side-image, echo = FALSE, fig.margin = TRUE}
knitr::include_graphics('pictures/volunteers.jpg')
```
+ From the data analysed in this report, the key findings are:
**Survey respondents enjoyed LEAFF so much that `r toString(paste0(txt_rating * 100, "%"))` said their experience was *Very good* or *Good*.**
**Survey respondents enjoyed LEAFF so much that `r toString(paste0(txt_recommend * 100, "%"))` of them will recommend a friend or colleague to attend LEAFF.**
**The majority of survey respondents are of the *`r toString(txt_ethnicity)`* ethnic group.**
**The top three reasons for why survey respondents wanted to attend LEAFF were *`r toString(txt_motivation)`*.**
**`r toString(paste0(txt_retention_new * 100, "%"))` of survey respondents said this is their first time coming to the festival, showing that LEAFF was `r toString(txt_retention_stay[2])` in attracting new audience members and retaining previous members.**