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File Sharing: What and How Effects on Music Sales.

In: Computers and Technology

Submitted By saurabh1106
Words 1877
Pages 8
File Sharing: what and how
Effects on music sales.

File sharing is the practice of distributing or providing access to digitally stored information, such as computer programs, multimedia(audio, images and video), documents or electronic books. It may be implemented through a variety of ways.In this paper we are discuss common methods of storage, transmission and dispersion include manual sharing utilizing removable media, centralized servers on computer networks,World Wide Web-based hyperlinked documents, and the use of distributed peer-to-peer networking.We consider the specific case of file sharing and it’s effects on legal sales of music .

1. Introduction
Files were first exchanged on removable media.Computers were able to accessremotefilesusing filesystem mounting and FTP servers.The mp3 encoding, which was standardized in 1991 and which substantially reduced the size of audio files, grew to widespread use in the late 1990s. In 1998, and Audiogalaxy were established,
The Digital Millennium Copyright Act was unanimously passed, and the first mp3 player devices were launched.
In June 1999, Napster was released as an unstructured centralized peer-to-peer system, requiring a central server for indexing and peer discovery. It is generally credited as being the first peer-to-peer file sharing system.
Gnutella, released in March, was the first decentralized file sharing network. In the gnutella network, all connecting software was considered equal, and therefore the network had no central point of failure. In July
The popularity of peer-to-peer file sharing applications such as Gnutella andNapster has created a flurry of recent research activity into peer-to-peer architectures. Although the exact definition of “peer-to-peer” is debatable, these systems typically lack dedicated, centralized infrastructure, but rather depend on the voluntary Participation of peers to contribute resources out of which the infrastructure is constructed.
Wether - "A majority of economic studies have concluded that file sharing hurts sales". A literature review by Professor Peter Tschmuck found 22 independent studies on the effects of music file sharing. Conclude that unauthorized downloads have a 'negative or even highly negative impact' on recorded music sales. 2. Background File sharing has become one of the most common on-line activities. File sharing occurs In networks which allow individuals to share, search for, and download files from one Another. A key property of these networks is that sharing files is largely non-rivalrous Because the original owner retains his copy of a downloaded file. This makes the cost of Sharing quite low. Moreover, there are network externalities, since more individualsimply a greater selection of files. Though the process of exchanging Files is similar in both systems, Napster and Gnutella differ substantially in how peers locate files
In Napster, a large cluster of dedicated central servers maintain an index of the files that are currently being Shared by active peers. Each peer maintains a connection to one of the central servers On receiving the results, the peer may choose to initiate a file exchange directly from another peer. There are no centralized servers in Gnutella, however. Instead, Gnutella peers form an overlay network by Forging point-to-point connections with a set of neighbors. To locate a file, a peer initiates a controlled flood of The network by sending a query packet to all of its neighbors. The Gnutella protocol includes ping
And pong messages that help peers to discover other nodes. Pings and pongs behave similarly to query/queryresponse Packets: any peer that sees a ping message sends a pong back towards the originator
Crawling the Peer-to-Peer Systems 1. The Napster Crawler
The Napster server cluster consists of approximately 160 servers; each peer establishes a connection with Only one server. When a peer issues a query, the server the peer is connected to first reports files shared by “local users” on the same server, and later reports matching files shared by “remote users” on other servers in The cluster. For each crawl, we established a large number of connections to a single server, and issued many Queries in parallel; this reduced the amount of time taken to gather data to 3-4 minutes per crawl, giving us a Nearly instantaneous snapshot of peers connected to that server. For each peer that we discovered during the Crawl, we then queried the Napster server to gather the following metadata: (1) the bandwidth of the peer’s Connection as reported by the peer herself, (2) the number of files currently being shared by the peer,
(3) theCurrent number of uploads and the number of downloads in progress by the peer
(4) the names and sizes of all the files being shared by the peer, and
(5) the IP address of the peer.
From these statistics, we verified that each crawl typically captured Between 40% and 60% of the local peers on the crawled server. Furthermore, this 40-60% of the peers that we Captured contributed between 80-95% of the total (local) files reported to the server. Thus, we feel that our Crawler captured a representative and significant fraction of the set of peers.
2. The Gnutella Crawler
Our crawler exploits the ping/pong messages in the protocol to Discover hosts. First, the crawler connects to several well-known, popular peers (suchAs Or Then, it begins an iterative process of sending ping messages with large ttls To known peers, adding newly discovered peers to its list of known peers based on the contents of received
Pong messages. In addition to the IP address of a peer, each pong message contains metadata about the peer,Including the number and total size of files being shared. We allowed our crawler to continue iterating for approximately two minutes, after which it would typically Gather between 8,000 and 10,000 unique peers . According to measurements reported by this Corresponds to at least 25% to 50% of the total population of peers in the system at any time.

3.Analysis of Algorithms, Techniques and Methodology The leading study to date is Liebowitz (2003). Liebowitz tries to explain annual trends in national sales using a wide variety of possible Factors including the macro-economy, demographics, changes in recording format and Listening equipment, prices of albums and other entertainment substitutes, and changes in Music distribution. He finds these factors cannot fully explain the decline in sales from 1999-2002 and therefore concludes that file sharing has reduced aggregate sales.
Our approach differs we directly observe file sharing Activities. Our results are based on a large and representative sample of downloads, in Which the individuals are generally unaware that their actions are being recorded.
File sharing Networks
File sharing Relies on computers forming networks which allow the transfer of data. Each computer (or node) may agree to share some files and has the ability to search for and download Files from other computers in the network. Individual nodes are referred to as clients if They request information, servers if they fulfill requests, and peers if they do both. We just discussed about p2p system above.
Set, we collected the titles of the individual tracks, information on performing
Artists and track time from (2003), an on-line media guide published by Alliance entertainment corp. We form indicators for whether the album has a track 8 Which is receiving heavy media attention in each week. Our indicator for frequent Commercial radio play is based billboard’s (2002) “top 50 airplay,” for heavy mtv Rotation based on the top twenty-five ranks listed in radio & records (2002), and for Widespread college radio play based on the top twenty ranks listed in cmj networks (2002). We also form weekly indicators for whether the artist is on tour based on concert Dates from the weekly trade publication pollstar.
Overview :
The servers were connected to T-3 lines which provided actual Internet transmission Speeds of several megabits per second for both uploads and downloads. The high-speed Connections ensured that a large number of search requests and downloads could be Handled in real time. The information on file transfers is collected as part of the usual log Files which the servers generate, and most users were not actively aware that they were Being monitored. Search lines describe what users are looking for, and transfer lines give The location of the file that is being transferred as well as the name of the file, which
Includes information on the artist and the song. Typical examples are:
[2:53:35 PM]: User evnormski "(XNap 2.2-pre3, 80.225.XX.XX)" logged in
[2:55:31 PM]: Search: evnormski "(XNap 2.2-pre3)": FILENAME CONTAINS "kid rock devil" MAX_RESULTS 200 BITRATE "EQUAL TO" "192" SIZE "EQUAL TO" "4600602"
"(3 results)"
[3:02:15 PM]: Transfer: "C:\Program Files\KaZaA\My Shared Folder\Kid Rock –
Devil Without A Cause.mp3" (evnormski from bobo-joe)
Empirical Strategy
Our goal is to measure the effect of file sharing on sales. We present a model of purchase And download behavior and highlight here the key implications. The
Simplest approach is to estimate simple pooled models of the form,
(1) Si X iBDi , where i is the album, Si is observed sales, Xi is a vector of album characteristics and Di is the number of downloads.
We find that file sharing has no statistically significant effect on purchases of the average album in our sample. Moreover, the estimates are of rather modest size when compared to the drastic reduction in sales in the music industry. At most, file sharing can explain a tiny fraction of this decline. This result is plausible given that movies, software, and video games are actively downloaded, and yet these industries have continued to grow since the advent of file sharing. While a full explanation for the recent decline in record sales are beyond the scope of this analysis, several plausible candidates exist. These alternative factors include poor macroeconomic conditions, a reduction in the number of album releases, growing competition from other forms of entertainment such as video games and DVDs (video game graphics have improved and the price of DVD players or movies have sharply fallen), a reduction in music variety stemming from the large consolidation in radio along with the rise of independent promoter fees to gain airplay, and possibly a consumer backlash against record industry tactics.26 It is also important to note that a similar drop in record sales occurred in the late 1970s and early 1980s, and that record sales in the 1990s may have been abnormally high as individuals replaced older formats with CDs
If we are correct in arguing that downloading has little effect on the production of music, then file sharing probably increases aggregate welfare. Shifts from sales to downloads are simply transfers between firms and consumers. And while we have argued that file sharing imposes little dynamic cost in terms of future production, it has considerably increased the consumption of recorded music. File sharing lowers the price and allows an apparently large pool of individuals to enjoy music.

3. Journal of Law and Economics& Billboard Magazine
4. Liebowitz, Stan (2002). “Policing Pirates in the Networked Age.
5. “Gnutella measurement project,” May 2001.

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