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statistics
This page considers statistics about spam.
It covers -
Statistics
about messaging systems are highlighted here,
with a broader discussion of network activity and measurement
challenges here.
how
much
There is little agreement regarding figures about -
- the
volume of spam sent to consumers
- the
volume received (not necessarily the same, as many ISPs
and organisations employ filters that deflect the junk
before it arrives in the recipient's in-box)
- the
volume actually opened by recipients
- growth
rates, the frequency of particular types of messages
and points of origin
One
reason for uncertainty is that many figures come from
vendors of anti-spam products/services. Particular announcements
by the anti-spam industry have received widespread attention,
particularly in the mass media, but been questioned. Another
reason is that volumes appear to vary significantly, with
US studies suggesting that recipients in the entertainment
and transport industries get a higher per capita number
of messages than those those in the health or construction
industries.
One study suggests that 2.8 billion direct marketing email
messages were sent in 1998, with - hold your breath -
that figure forecast to rise to 236 billion in 2005. US-based
AOL estimated in 2001 that spam accounted for 30% of email
to its subscribers, between 5 and 8.5 billion messages
pa. By mid-2003 other ISPs and institutions were claiming
that spam accounted for up to 45% of incoming messages.
Filter vendor MessageLabs claimed in May 2003 that 55.1%
of all messages scanned were spam; competitor SpamTrap
announced that 55.8% of messages tracked with its service
were spam.
In March 2006 the Messaging Anti-Abuse Working Group (MAAWG),
a group of ISPs, reported (PDF)
that 80% of email to its sample of 100 million email boxes
was spam, a figure presented by some journalists as "80%
of Internet traffic".
A January 2001 study
from the European Commission suggests that internet users
pay 10 billion euro in connection costs just to receive
spam. Other studies have claimed that at the beginning
of 2002 some ISPs were now receiving between 4 and 20
items of spam for every genuine message.
Anti-spam vendor Brightmail claimed that of 5.5 million
unique UCE messages identified through its service in
November 2002, over 75% were solicitations for consumer
products, financial services and adult content, with 25%
regarding online scams or spiritual, health and other
services. In July 2003 Brightmail projected
at
least 1 in 2 of all emails that individuals and businesses
receive will be spam by September 2003 or earlier, and
a fifth of spam in the UK will be pornographic.
An
August 2001 Gallup Poll report
indicates that most US email users say that up to 30%
of messages they receive are spam; 39% say they receive
more than that, including 18% who say that spam comprises
at least half their email. 42% said they "hate it," 45%
said spam is "an annoyance, but do not hate it," while
the rest have no strong feelings either way (9%) or sometimes
find the information contained in spam useful (4%).
In December 2008 Cisco claimed that nearly 200 billion
spam messages (90% of all email) were sent each day, with
17.2% from the US, 9.2% from Turkey, 8.0% from Russia,
4.7% from Canada, 4.1% from Brazil, 3.5% from India, 3.3%
from South Korea, 2.9% from Germany and 2.9% from the
UK.
what sort
Some recipients assume that everyone gets the same quantity
of spam or the same types of electronic junkmail. That
is not the case.
One reason is that filtering of mail by ISPs or other
intermediaries (eg corporate network managers) varies
considerably.
Some use a 'light touch' approach; others filter zealously,
sometimes to the extent that recipients complain that
legitimate messages have been excluded. Some rely on blacklists.
Some use content analysis mechanisms that attempt to identify
spam on the basis of a message's text/attachments (eg
inclusion of 'cialis' or 'viagra' tags the message as
junk). Some rely on exclusion of messages addressed to
all/multiple addresses within a domain, particularly those
with false addresses.
Variation in the volume/type of spam received also reflects
the 'exposure' of the address (eg whether it can be scraped
from a web site, appears in a public newsgroup or in the
address book of a personal computer that has been captured
by a spammer) and the extent to which the spammer is targeting
particular domains or demographics (eg people who have
supplied contact details to adult content sites).
Some spammers send messages indiscriminately, for example
to every address in a large list of real addresses or
to machine-generated lists of possible addresses for particular
domains.
As with conventional direct marketing, the cost of lists
can reflect factors such as the accuracy of the data,
the perceived value of particular demographics and the
uniqueness of the list (some lists come cheap simply because
overuse in the past has led to abandonment of many of
the addresses after recurrent spamming and to inclusion
of the information in filters maintained by some ISPs).
Consumer Affairs Victoria for example analysed the type
of spam received by one address in January 2005 and May
2008. The analysis was small-scale, covering 8,200 emails.
The breakdown of messages was as follows -
-
Nigerian 13.7%
-
Lottery and other prizes 2.3%
- Pharmaceutical
- adult (Viagra etc) 11.4%
-
Other pharmaceutical (eg vitamins and alternative health
potions) 2.9%
- Phishing
9.7%
-
Software and computer hardware 8.0%
- Watches
and jewellery 7.4%
-
Adult content 6.3%
- 'Wealth
creation', business ventures, business seminars 5.1%
- Financial
services such as mortgages, loans etc 1.7%
- 'Work-at-home'
and job offers 2.3%
-
Miscellaneous products such as posters and books 3.4%
- Brides/dating
agencies 1.7%
-
Political 0.6%
-
Music/games downloads 0.6%
- Malware
12.6%
- Advertising
an apparently legitimate product 10.3%
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