68,436 research outputs found
UNDERSTANDING MUSIC TRACK POPULARITY IN A SOCIAL NETWORK
Thousands of music tracks are uploaded to the Internet every day through websites and social networks that focus on music. While some content has been popular for decades, some tracks that have just been released have been ignored. What makes a music track popular? Can the duration of a music trackâs popularity be explained and predicted? By analysing data on the performance of a music track on the ranking charts, coupled with the creation of machine-generated music semantics constructs and a variety of other track, artist and market descriptors, this research tests a model to assess how track popularity and duration on the charts are determined. The dataset has 78,000+ track ranking observations from a streaming music service. The importance of music semantics constructs (genre, mood, instrumental, theme) for a track, and other non-musical factors, such as artist reputation and social information, are assessed. These may influence the staying power of music tracks in online social networks. The results show it is possible to explain chart popularity duration and the weekly ranking of music tracks. This research emphasizes the power of data analytics for knowledge discovery and explanation that can be achieved with a combination of machine-based and econometrics-based approaches
Topicality and Social Impact: Diverse Messages but Focused Messengers
Are users who comment on a variety of matters more likely to achieve high
influence than those who delve into one focused field? Do general Twitter
hashtags, such as #lol, tend to be more popular than novel ones, such as
#instantlyinlove? Questions like these demand a way to detect topics hidden
behind messages associated with an individual or a hashtag, and a gauge of
similarity among these topics. Here we develop such an approach to identify
clusters of similar hashtags by detecting communities in the hashtag
co-occurrence network. Then the topical diversity of a user's interests is
quantified by the entropy of her hashtags across different topic clusters. A
similar measure is applied to hashtags, based on co-occurring tags. We find
that high topical diversity of early adopters or co-occurring tags implies high
future popularity of hashtags. In contrast, low diversity helps an individual
accumulate social influence. In short, diverse messages and focused messengers
are more likely to gain impact.Comment: 9 pages, 7 figures, 6 table
Entertainment in the 21st Century: Is an Independent Networked Multimedia Production and Promotion Firm a Viable Business Option in the Modern Entertainment Industry?
âArtists are being stifled by the âmajor labelâ stance that exclusively demands whatâs ours is ours and can only be handled by us. It should be more about creative freedomâ (Monstercat Manifesto). Over the past fifteen years, we have witnessed how the internet has changed how entertainment is distributed and consumed. This has led to a change in behavior from major entertainment production firms, and has given way to the surge of independent labels and production houses. Now, entertainers can lead successful careers by reaching their audience through digital platforms, successfully decreasing production and distribution costs. Consumers can find an unlimited amount of ad-supported content that they can access for free. Understanding these change is vital in finding and solving the problems these changes have produced
The Skipping Behavior of Users of Music Streaming Services and its Relation to Musical Structure
The behavior of users of music streaming services is investigated from the
point of view of the temporal dimension of individual songs; specifically, the
main object of the analysis is the point in time within a song at which users
stop listening and start streaming another song ("skip"). The main contribution
of this study is the ascertainment of a correlation between the distribution in
time of skipping events and the musical structure of songs. It is also shown
that such distribution is not only specific to the individual songs, but also
independent of the cohort of users and, under stationary conditions, date of
observation. Finally, user behavioral data is used to train a predictor of the
musical structure of a song solely from its acoustic content; it is shown that
the use of such data, available in large quantities to music streaming
services, yields significant improvements in accuracy over the customary
fashion of training this class of algorithms, in which only smaller amounts of
hand-labeled data are available
The Implications of Viral Media & Advocacy: Kony 2012
This research paper analyzes the video âKony 2012â as an example of advocacy film making and viral media. By analyzing critical sources, I draw conclusions as to why this video became the most viral video of all time and how other advocacy groups can use this phenomenon to learn about viral advocacy media. Using data from LexisNexis Academic, I track the popularity of âKony 2012â via different forms of media (blogs, news articles, etc.) and compare my data to prior research conducted on social media sites. Ultimately, I will find that several key characteristics can be pinpointed as the primary cause for the filmâs viral ability; including a pre-existing network of followers and the filmâs ability to spread through social and traditional media. Additionally, I will conclude that the filmâs inconsistent facts and the organizations behaviors played a role in the filmâs demise
Cultural transmission modes of music sampling traditions remain stable despite delocalization in the digital age
Music sampling is a common practice among hip-hop and electronic producers
that has played a critical role in the development of particular subgenres.
Artists preferentially sample drum breaks, and previous studies have suggested
that these may be culturally transmitted. With the advent of digital sampling
technologies and social media the modes of cultural transmission may have
shifted, and music communities may have become decoupled from geography. The
aim of the current study was to determine whether drum breaks are culturally
transmitted through musical collaboration networks, and to identify the factors
driving the evolution of these networks. Using network-based diffusion analysis
we found strong evidence for the cultural transmission of drum breaks via
collaboration between artists, and identified several demographic variables
that bias transmission. Additionally, using network evolution methods we found
evidence that the structure of the collaboration network is no longer biased by
geographic proximity after the year 2000, and that gender disparity has relaxed
over the same period. Despite the delocalization of communities by the
internet, collaboration remains a key transmission mode of music sampling
traditions. The results of this study provide valuable insight into how
demographic biases shape cultural transmission in complex networks, and how the
evolution of these networks has shifted in the digital age
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