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Music has long been considered a universal language. Unlike spoken word, the diverse sounds of music ascend meaning across country borders, societies, and drastically different cultures. The pitch, rhythm, timbre, texture, dynamics, tones, and sequence that create a tune hold the unique ability to communicate ideas where linguistic limitations fall short. Music is a unifier. With as many styles and variations as humankind itself, there is not a single person in the world that is not impacted by the sound of music. For this reason, music is a reflection of the cultural values and societal norms of the time period and place it was created in. Researching the changing trends of music that was most listened to in a defined place in history give scholars a valid and enlightening window into better understanding people’s lives during that era. By analyzing these patterns, researchers are able to draw connections between important historical events and the sounds that were popular during that generation. Overall, analyzing music is a tool that uniquely informs historians on all aspects of life including the cultural, political, economic, and societal landscape of the time of production of a particular song. In order to better understand history from the early 20th century into modern times, it’s imperative to investigate the development of musical style. The data set we have studied is called The Million Song Dataset. Out of the million songs, we reduced our sample size to only 4,681 for practicality purposes for this project. The data set provides information about each song’s production location, date it was created, artists who created the song, along with technical information such as tempo, tone, key, length, and more. This is a relevant and valuable source because it grants researchers the ability to see a large amount of data per song, with a large enough sample size of songs to draw hypotheses and craft arguments.

Place in Literature

The wide variety of sources examined for this research has informed our project on various scholarly opinions and arguments. Kim Kyle’s Los Angeles Times article “The Evolution of Music: How Genres Rise and Fall over time” argues that there are defined shifts in popularity between music genres over time, with some genres on a more oscillating scale and others much more dramatic. Similar to Kyle, the article “Understanding Media and Culture: an Introduction to Mass Communication” from the University of Minnesota argues that people’s preferred music genres change rapidly over time. Matthias Mauch (along with 3 other contributors) wrote the article “The Evolution of Popular Music: USA 1960 - 2010” which argues a similar point to Kyle and the University of Minnesota. Mauch’s article discusses that popular music in the USA changed due to specific cultural norms and likes. Overall, these three articles agree on the hypothesis that some genres of music are incredibly volatile and respond to cultural dynamics while others are more consistent over time. Rebecca Morelle’s article “Pop Music Marked by Three Revolutions in 50 Years” argues that pop music has evolved continuously since the 1960s in the USA, pointing to three distinct stylistic ‘revolutions’ occurring around 1964, 1983, and 1991. Evolver.fm’s article “What Makes a Hit Song? Science Tries to Find the Answer” argues that there are specific features that are common characteristics across all popular songs. They employ more of a scientific approach, analyzing BPM (beats per minute) and tempo. Daniel Silver’s article “Genre Complexes in Popular Music” argues that genre conventions exist that structure popular music, and these conventions differ across musical styles. Overall these articles examine more exact music engineering related reasons for why music becomes popular, along with noting explicit dates when noticeable popularity shifts happen. Interiano Myra’s article “Musical trends and predictability of success in contemporary songs in and out of the top charts” discusses the acoustic features of a song and how those features relate to the song’s popularity. Similarly, Alex Wilson and Bruno Fazenda’s article “Perception of Audio Quality in Productions of Popular Music” from the Acoustics Research Centre at the University of Salford, argues that the perception of a song’s quality can be affected by numerous factors such as loudness and dynamic range compression. In the book Soundtracks by John Cornnell and Chris Gibson, the authors summarize and track the landscape of popular music’s change over time. These three sources argue that acoustic features along with several other musical factors influence how a song becomes popular, and when a song becomes popular. Marc Hogan’s article, “Uncovering How Streaming Is Changing the Sound of Pop,” provides a very interesting insight into the current landscape of popular music, claiming that streaming services such as Spotify, have a large hand in shaping what people listen to based off of their recommendation algorithms. By the same token, Paul Resnikoff’s article “What Are The Most Popular Music Genres?,” explores general trends in the listening habits of America, showing not only what people are listening to but also how. Another article that ties in to America’s current soundscape is Eric Weisbard’s “Beyond Category? Never! The Game of Genres in Popular Music,” which is a critique of two books that discuss how communities create musical genres. These three sources offer a refreshing perspective as young music listeners continue to change the way people think about and listen to music. The final source on our bibliography is Sheila Whiteley and Jedediah Sklower’s Countercultures and Popular Music. The main point of this book is that one can trace the changes in popular music by analyzing the social trends of the time, particularly of the counterculture and their musical reaction to the social and political injustices of their day. Little to none contradictions exist in the literature we are using for our research. All sources to point to the central idea that music trends speak to historical progression. Scholars all agree on this change over time. Some questions still remain. Often songs that seem out of the usual prediction for hits make it to the top charts. Also, it would be interesting to further explore the role of new and emerging technology in the music space, and how this new tech is making it easier to produce music without the need of music labels and the traditional thru fare artists had to take back in time.

Significance

Music is a huge part of our everyday lives, hence it is highly representative of the people in a certain time period. By analysing the songs and the music trends, we can gain insight into the popular culture and beliefs of society. Since music is inherently intertwined with the culture of a society, it can give us information about the state of that society the same way that literature, or any other art form can.This project is important because through tracking music, we are able to better understand how these trends change throughout history. This project could make an intervention in the field by exposing trends in society that may not have been as clear before. Additionally, our project would visualize data to provide evidence and explore our initial research questions in a way that has not been done before. What sets this project apart from previous work in the field is the sheer mass of data. The million song dataset that we worked from was unprecedented in terms of total number of songs indexed, while we are only working with a subset of this data, it is still much larger than what was been examined in previous studies. In addition, connecting trends in music we will be able to visualize cultural norms that were not able to be analyzed as such before. Everyone listens to music, and most are familiar with what music is currently popular. However, it is not until we are removed from our present biases that we can see clearly pick out trends. It is also not until then that we can understand what drove these trends and what the resonating effects of these trends was. Additionally, data visualizations are powerful since they resonate with their viewers much more strongly than an excel sheet full of information. Humans don’t react to numbers, humans react to narrative. Data visualizations allow us to turn numbers into narrative.

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