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Deconstructing Book-to-Film Franchises

Page history last edited by Derek Isa 9 years, 3 months ago

Deconstructing Book-to-Film Franchises

By Derek Isa

 

            The Book-to-Film Franchise project from UCSB aimed to discover the secret behind creating a successful book-to-film franchise.  This project group, comprised of five Film and Media Studies majors from Santa Barbara, looked at a set of film adaptations from two popular book series.  The novel series Harry Potter, written by renowned British author J.K. Rowling, was used as the standard for a “successful” book-to-film franchise.  In order to establish the Potter franchise as “successful,” the project team initially needed to define the term in this context.  As a result, the team came up with three categories to define success: reviews (both consumer and critical), social impact, and box office achievement.  The second novel series, C.S. Lewis’ Chronicles of Narnia, was used as a comparison to the Potter franchise to further demonstrate the accomplishments of the latter.

            For time constraint purposes, this project chose to look at only three stories from each of the series.  The Book-to-Film Franchise team picked Sorcerer’s Stone, Goblet of Fire, and Deathly Hallows (pt. 2 of the films) from the Harry Potter novels.  The Lion, the Witch, and the Wardrobe, Prince Caspian, and Voyage of the Dawn Treader were specifically selected from the Chronicles of Narnia series to match the chosen Potter stories in certain factors.  One of these factors included the movies’ chronological release.  Identically, Sorcerer’s Stone and The Lion, The Witch, and the Wardrobe were the first books, as well as films, of each series.  The same chronological factor impacted the selection of Deathly Hallows (pt. 2) and Voyage of the Dawn Treader.  However, this chronological aspect only applied to the movies because the Narnia franchise has only produced three of the seven books.  In regards to picking a Potter story to compare to Prince Caspian, this project decided on Goblet of Fire.  This movie made logical sense because the year it was released in coincided with the Lion, the Witch, and the Wardrobe (2005).

            Following the selection of stories, the group chose three digital humanities tools to gather information about two of the three categories of success.  The three tools the Book-to-Film Franchise team used were Umigon, Netlytic, and Sentiment Analysis.  While the use of a film-based tool would have provided a better understanding of what made the movies themselves better, no such helpful tools existed.  Cinemetrics, a complicated tool designed to evaluate the color and movement of a movie, is the closest the group came to finding a useful film-based tool.  However, after attempting to download the programs needed to run the tool failed, this project decided to direct its focus to the reception of the movies.  By doing so, the project team utilized text-based methods to evaluate the stories.

            The first tool, Umigon, gathers text from the social media site Twitter and sends each tweet through a sentiment analysis tester.  After analyzing each tweet, the tool gives a rating of ‘positive,’ ‘negative,’ or ‘neutral’ sentiment.  An advantage of Umigon is its ability to analyze a vast quantity of tweets based on keyword searches and usernames of Twitter accounts.  Unfortunately for the Book-to-Film Franchise project team, it was difficult to narrow down the search of Harry Potter and Chronicles of Narnia tweets from the past decade and a half.  Also, most of the tweets found were based on the books instead of the movies.  Furthermore, the tweets that were found and put through the sentiment analysis test came out neutral.  Yet, one intriguing piece of information did arise from exploring Twitter for adequate tweets.  The Harry Potter franchise has a verified Twitter account called @HarryPotterFilm, which has about 1.5 million followers.  Conversely, the Narnia franchise does not have any official account.  This is important because it shows Potter’s social relevance even three years after the release of the final film.

            Netlytic is a tool used to assess mass quantities of social network threads and separates the words out into a visual medium by the words’ frequency.  For example, this project researched the YouTube comments from the trailers of each of the six selected movies.  The comments from the Harry Potter trailers generally consisted of conversations about the film series itself, except for Goblet of Fire, where comments included topics of Robert Pattinson.  This spike in Pattinson’s name was a probable result of his rise in popularity following the release of Twilight.  On the other hand, the conversations on the Narnia trailers rarely focused on the movies, and ranged from Christian aspects to ‘Harry Potter,’ and to even ‘Harry Styles.’  These results supplemented the Umigon findings and further confirmed the social dominance of Harry Potter over Narnia.

            Sentiment analysis, conceptually used in Umigon, analyzes given text and rates the sentiment on a scale of ‘very negative,’ ‘negative,’ ‘neutral,’ ‘positive,’ and ‘very positive.’  The Book-to-Film Franchise project employed this tool by putting a book review of the six stories through the analysis.  Overall, the sentiment results of the book reviews came out positive for both of the series.  Each review followed a general pattern: a positive assessment of the book as a whole, followed by a specific critique of a problem within the novel, and finished up by a positive recommendation to readers of the review.  However, a primary issue emerged while further exploring the results of the sentiment tests.  While Sentiment Analysis does correctly classify certain sentences and phrases, the program lacks the ability to distinguish between negative words and an overall negative sentiment.  For instance, in the review of Sorcerer’s Stone, the critic describes Uncle Vernon and Aunt Petunia as ‘odious,’ which yielded a ‘very negative’ sentiment.  Clearly, the word ‘odious’ was not describing the book as a whole but a minor character.  This is problematic because a text could yield an overall negative result, while actually having a positive sentiment.  Also, the tool also limits the amount of text it is able to analyze at once—200 lines—which makes it hard to look at large bodies of text.

            Continuing to look at reviews, the project team decided to take a general assessment of film reviews from the online movie critic site: Rotten Tomatoes.  This approach, as opposed to the sentiment analysis test of the book reviews, did not involve using a digital humanities tool.  The online site follows a scale, referred to as the “tomatometer,” consisting of three levels: ‘certifiably fresh,’ ‘fresh,’ and ‘rotten.’  This meter takes into account the reviews of hundreds of movie and television critics, some of whom are well renowned in the film industry.  A movie is given a ‘rotten’ score if 59 percent or fewer critics negatively rated it.  Subsequently, a film is ‘fresh’ when 60 percent or more of the ratings yield a positive result.  To achieve a ‘certifiably fresh’ rating, the “tomatometer” must reach 75 percent or higher, with the added requirement of having a minimum of 40 reviews and five reviews from ‘top critics.’  For the purpose of measuring consistent critical success, the project team chose to gather the results from all eleven Narnia and Potter movies.  The “tomatometer” ratings for each film indicated just how consistent Potter’s critical success was.  Every one of the eight movies from the series achieved a ‘certifiably fresh’ score.  Comparatively, Narnia’s critical prosperity steadily and consistently declined for each of the three movies.  While the Lion, the Witch, and the Wardrobe attained a ‘certifiably fresh’ rating, Dawn Treader dropped all the way to a ‘rotten’ score—49 percent.

            Switching the focus of success, the Book-to-Film Franchise project researched the box office numbers of the six specific films.  Once again, the team did not use a tool to understand the general data gathered.  Overall, the Potter movies, as expected, blew Narnia out of the water both domestically (United States) and worldwide.  Specifically, the first Narnia earned around 26 million dollars less domestically than Sorcerer’s Stone (Potter’s first film) and over 220 million dollars less worldwide.  Furthermore, the most recent film releases of each franchise—Harry Potter and the Deathly Hallows: Part II and The Chronicles of Narnia: The Voyage of the Dawn Treader—exemplify the former’s dominance and the falling off of the latter.  The finale of the eight-movie series grossed nearly 200 million dollars more domestically than the most recent installment for Narnia.  Although the final film of a series typically earns more than its predecessors, the lowest grossing Potter film still brought in over 100 million more than Dawn Treader—the least grossing Narnia movie.  Through the box office numbers alone, it is clear just how dominant Rowling’s riveting stories were over Lewis’ tales.

            As Film and Media Studies majors at a University, the members of the team decided to do a group analysis of the project topic.  With the establishing idea that Harry Potter set the standard for a successful book-to-film franchise, the group viewed the Narnia series as an attempt to recreate the Potter phenomenon.  By analyzing the mise-en-scene—the visual theme and aspects—of the movie, it is clear to see the influence the imagery of Potter had on its successor.  For instance, the color scheme and symbol of the protagonists’ army closely resembles Harry Potter’s wizardry house, Gryffindor.  Also, the train the Pevensie children take to their uncle’s home is almost identical to the Hogwarts Express, with the latter having more detailed labeling on it.  Yet, despite following many of the visual imageries of the Potter world, there were areas of its stories the Narnia franchise came up short in.

            One of these areas was the narrative perspective of the Narnia story.  The primary strength of J.K. Rowling’s series is making her protagonist highly relatable, which allows the reader to become easily immersed in the narrative.  Harry Potter, like most heroes, has a deeply troubled past, but also experiences common human traits—a lack of desire to be ‘the chosen one,’ nerves when attending a new school, and general uncertainty about himself.  The Pevensie children, on the other hand, get portrayed as spoiled and rather immature despite the story’s direction toward an adult understanding.  Due to these unfavorable traits, an emotional connection between the viewer and the Narnia protagonists becomes immensely difficult to achieve.  Focusing further on the protagonists, Harry Potter is arguably the sole protagonist and, by far, the concentration of the driving action in the plot.  As for Lewis’ story, there are four protagonists, which prevents the audience to attach to a specific character and perspective.  Also, following Prince Caspian, two of the protagonists, Peter and Susan, are no longer an integral part of the plot.  In their place, the Pevensie’s cousin is introduced, who proves to be just as unlikeable as the four other youths.

            The other area of the stories, arguably the toughest challenge for film adaptations of popular books, was staying faithful to the novel.  Avid readers take offense to the director and producer’s failure to properly recreate the magic of the text.  These amateur critics have a valid argument; if the book were such a resounding success, why would filmmakers attempt to stray away from it?  The other side of the fence would argue that the difficulty lies with the style of writing and the text itself.  For this exact reason, the group hypothesized that Rowling’s heavily descriptive style of writing painted a clearer picture.  Lewis, on the other hand, wrote allegory pieces, which would lead to an array of interpretations of the text.  Therefore, while both Potter and Narnia filmmakers might have remained faithful to the text, the style of writing of one was far more suitable for an adaptation than the other.

            While the Book-to-Film Franchise team did gather valuable information for its topic of focus, the project was, under many circumstances, a prototype.  Thus, a plethora of improvements can be made to this project to yield even better results.  Before general enhancements take place, a lift of limitations must occur as well.  The chief limitation had to be the time constraints of this project.  Without a time constraint, there is an exponential possibility of how much information a group can gather related to this topic.  Another drawback, mostly due to the lack of a million dollar budget, was the sheer lack of manpower to gather sufficient evidence in the five weeks of work.  With a team three or four times the size of the Book-to-Film Franchise team, specific focuses could be assigned to a group of individuals to hopefully increase the amount of data collected.  Sticking with the hypothetical situation of having a sizable budget, a team of designers and programmers could be assembled to create a tool intentionally directed at film critiquing.  Purely theoretically speaking, a tool designed to critique a movie on narrative structure, characterization, mise-en-scene, and other specific film analysis categories, would be optimal for a project of this nature.  However, despite these categories having certain standards, much of film critiquing is subjective and more accurate from a human.

            Though theorizing about the “perfect” film analyzing tool can be intriguing, it may not be all that practical.  Therefore, there are developments that can be made to existing tools, film and text alike.  Cinemetrics, a visual-based tool that displays a movie’s color scheme and character movement in a circular spectrum, has the most potential to be a viable tool for studying films.  The primary improvement for this tool is the creation of a user-friendlier interface.  Currently, in order to take advantage of Cinemetrics’ highly advanced software, a user must download complicated script that would take a lot of research to understand and run.  Another possible practical tool, this time with a focus on the reception of movies, is the tool known as Reelmeasures.  This tool measures the impact of a film beyond the box office numbers—a particularly helpful tool for this project’s purpose—based on a set of factors that vary in importance based on the user’s desire.  Unfortunately, this tool contains only specific films and sets the location for domestic reference to Australia.

            For the text-based tools, issues with Sentiment Analysis have been previously discussed, but Netlytic and Umigon have its share of issues and areas of improvement as well.  Netlytic, the tool that analyzes social network threads, has one primary issue that the creators can change.  In regards to YouTube comments, an obscene amount of spam accounts comment on popular videos.  This problem leads to a diluted result for how relevant certain words are for a thread.  Umigon, also targeting social networking (Twitter), in a sentiment analysis-type method, likewise has one pivotal issue.  With an exponentially growing database of tweets, it is hard to access and store all this information in one place.  As a result, users might have trouble finding relevant tweets that pertain to the topic of focus they are researching.  This issue plagued the Book-to-Film Franchise team from finding any solid evidence for its project.

 

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