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Many scholars anticipate that online interaction will have a long-term effect on the evolution of language, but little linguistic research yet addresses this question directly. In sociolinguistics, social network relations are recognized as the principal vehicle of language change. In this paper, I develop a social network approach to online language variation and change through qualitative and quantitative analysis of logfiles of Internet Relay Chat interaction.
The emerging sociolinguistic relationship is more complex than what is predicted by current sociolinguistic theory for offline interaction, suggesting that sociolinguistic investigation of online interaction, where more detailed and fine-grained information about social contacts can be obtained, may offer unique contributions to the study of language variation and change.
Both popular wisdom and professional scholarship in a range of academic disciplines make a diversity of predictions about how the Internet will shape our lives and our language. If we are to understand truly how the Internet might shape our language, then it is essential that we seek to understand how different varieties of language are used on the Internet.
In sociolinguistics, social network relations — the variety and frequency of contacts among people in a society — are recognized as the principal vehicle of language change. Likewise, people who have less contact with one another tend to share fewer linguistic features with one another.
Thus, to answer questions about how the Internet might affect the language that we use, we need to ask how it affects social contact among individuals, and what kinds of linguistic features that contact transmits to users.
There is also an urgent need to study language contact on the Internet; the rapid expansion of the Internet, and changes in the technology and the ways it is used make the Internet a very dynamic social force. Moreover, where sociolinguistics is concerned, theories of language contact and change developed through offline observations can be tested and refined through exploiting the rich data made available by persistent, digital text.
Prior to the existence of the Internet, sociolinguists had to rely on crude approximations of frequency of contact to construct social networks. With the potential to log digital texts, a researcher can now compile a comprehensive corpus of interactions taking place among a selected group of people on any mode of computer-mediated communication, and from that record be able to identify recurrent producers and recipients of messages; in this way, a very detailed understanding of the frequency and nature of contact among members of a group can be constructed.
One example which illustrates well the importance of the Internet for the study of language contact is the recent explosion in the popularity of Internet Relay Chat IRC [ 20 ]. Like other computer-mediated communication CMCIRC is hosted by networks of servers that are globally distributed, so participants on IRC come from many different national backgrounds. What sets IRC apart from other modes of CMC is that interaction is conducted almost in real-time: all participants the strength of absent ties social integration via online dating an interaction must be electronically present at the same time, and messages are immediately transmitted through the intermediate servers to all participants, wherever they may be.
Thus, IRC is characterized by much shorter propagation delay than Usenet news and Listserv messages. In addition, IRC is multi-participant, and message length is very short typically one or two lines so that IRC interaction is similar to the strength of absent ties social integration via online dating face-to-face conversation.
Using IRC, people who are located in geographically distant locales, who are of different national and linguistic backgrounds, and who might otherwise never come into contact, can engage in real-time interactions that resemble the immediacy of in-person face-to-face encounters, the strength of absent ties social integration via online dating. Unlike most face-to-face interaction, the strength of absent ties social integration via online dating, IRC interaction is constant.
Since people must necessarily attend to other aspects of life, such as work or school, the participants of an IRC channel are constantly in flux. Nonetheless, the strength of absent ties social integration via online dating, IRC channels appear to develop a readily identifiable character.
Interaction on a channel comes to center on topics that are related to the channel theme. Certain participants regularly return to the same IRC channels, to resume and maintain relationships they have initiated there.
And recurring patterns of language use develop. On the channel india, for example, I have noted several characteristic patterns of such language use, including the following five: 1. Such linguistic developments often arise entirely through interaction on the IRC channel. Given that participants on IRC may be separated by linguistic and international boundaries, and given that the body of participants on a channel is constantly changing and that many have never met face-to-face, how are such norms established and propagated?
This approach is that of social network studies in sociolinguistics. In prior social network studies, the linguistic variables tend to be more thoroughly studied than the social network relations. What sociolinguists tend to do is to analyze network relationships using other information, such as the mutual naming of friends [ 10 ]. These techniques provide an approximation of frequency of contact, without requiring that the researcher observe such contact directly.
In some cases, notably the work of Milroy [ 11 ] and Milroy and Milroy [ 12 ], researchers use participant observation to study social network relationships more directly, but this requires an extensive research commitment on the part of the researcher, and still does not permit the researcher to observe directly the frequency of linguistic interaction between any pair of participants.
With online interaction, the social network analysis can be based on a record of interaction contained in a log of online conversation. In this way, only the linguistically relevant social contacts can be studied. At the same time, the textual log of interaction allows the frequency of interaction to be used directly in studying the spread of linguistic variables. Sociolinguistic theory generally recognizes that social network ties vary in quality.
two people being both siblings and business partnersand territorially based groups e. neighborhood gangs. These different types of network ties are associated with different norms for the use of linguistic variables. Individuals at the center of networks with predominantly strong ties tend to use more non-standard, vernacular linguistic variants. People at the periphery of the same networks, with fewer of the same strong ties tend to use fewer vernacular variants.
Strong ties thus tend to enforce non-standard, vernacular linguistic norms. Conversely, people who have predominantly weak ties tend to have higher incidence of variants associated with the recognized standard variety. These patterns have led Milroy and Milroy to speculate that linguistic changes in the direction of the standard variety are propagated through weak network ties, while changes diverging from the standard variety in the direction of vernacular, non-standard varieties are propagated through strong network ties [ 11 ].
Indirect methods of studying social network ties, the strength of absent ties social integration via online dating as mutual naming, the strength of absent ties social integration via online dating, mostly reveal strong-tie relationships, the strength of absent ties social integration via online dating, leaving weak-tie relationships that are harder to study. Strong and weak network ties can potentially describe any sort of social interaction; if we use these notions to describe the social contacts made through IRC, then we can make predictions about the influence of IRC on language change.
Given that IRC participation is transient and constantly changing, and given that the participants on an IRC channel tend not to be territorially localized, we might expect the social network relationships expressed on IRC to be dominated by weak ties, the strength of absent ties social integration via online dating, and therefore to promote changes in the direction of the prestige variety.
While the IRC social networks formed this way are not territorial in the literal sense, they can have territorial interpretations, where the territory is a particular channel or set of channels. This territoriality is expressed through built-in structural asymmetries among users inherent in the IRC medium.
The first person to join a channel on IRC creates the channel and becomes the strength of absent ties social integration via online dating first operator. Thus, operators collectively and cooperatively define the boundaries of the social interaction on the channel. When a bot is opped, it may in turn automatically grant ops to channel participants especially the bot's owner whose names and passwords are stored in a database, or automatically execute actions that the owner and other operators may desire, such as kicking and banning other participants, or de-opping certain operators usually in preparation for kicking and banning them [ 20 ].
In this way, a two-tiered social system is maintained such that members of the upper tier operators and especially bot owners have more or less guaranteed privileges on the channel. Members of the lower tier the non-operators, ordinary users and newbies are always at the mercy of the operators, whose actions range from benevolent to capricious [ 5 ].
All these patterns of social differentiation have concrete implications for the tie strength experienced by different participants on a channel. Operators will tend to be regular participants with strong ties to one another and perhaps others. Since IRC messages are typed at a keyboard, there is a tendency to use conventions of written English, particularly spelling. Yet, as indicated in examples 1—5, a number of distinctive IRC spelling practices have emerged some of which can be found on many channels.
The practices in examples 2, 3 and 4, namely substituting the letters u and r for the English words you and are, and substituting z for s, especially in word-final position, are three such IRC spellings.
Finally, when a channel such as india has a regional or cultural theme, it is common to find a language like Hindi being used to mark in-group identity, much as is found offline see [ 13 ] and references therein.
Since in-group identity characterizes strong-tie social networks, we might expect such languages to be most common among the stronger ties on a channel.
But, are patterns of language variation on IRC — in the use of languages like Hindi, in IRC spellings, and in the use of obscenity — in fact correlated with the density of social interaction among participants of a channel? Does the preponderance of weak ties on IRC influence language use in any way?
And what can these patterns tell us about the nature of social interaction on IRC? To address these questions I conducted an exploratory investigation of social networks and language variation on the channel india on EFNet IRC. The largest number of participants connect from the US, the UK and Canada, although some also connect from other countries such as Indonesia and Thailand.
The community of india is thus a virtual community [ 17 ], in that its participants are widely distributed geographically and interact principally on-line. On the one hand there is the bilingual culture of expatriate Indian nationals. Many Indian expatriates reside in English-speaking countries and are fluent speakers of English.
Among the languages of India, Hindi holds a dominant position, both numerically and in social status, as it is the language of the national the strength of absent ties social integration via online dating and of the largest linguistic group in India.
On the other hand, younger members of the Indian expatriate community are immersed in the cultures of the local youth. In Australia, the US and the UK, this means that they attend public schools with English-speaking youth, where they are exposed to popular culture, and are expected to integrate into the dominant culture. Interaction on india was recorded for a complete hour period by connecting with an IRC client program and capturing the entire session to a log file.
A typical portion of the log appears as in Example 6, showing the different types of messages that appear on a user's screen when connected to the channel e-mail addresses have been changed to avoid identifying individual participants. sg has.
ca has joined. edu has. net has. Each line of the log file was coded as one of four message types: system messages, commands to bots, participant turns and actions. Lines that begin with a user's nick between angle brackets are participant turns. These lines are typed directly by users, except for the bracketed nick, which the system the strength of absent ties social integration via online dating. Actions are usually employed to present a message in a third-person narrative voice.
Many are transitive and involve other participants on the channel, and so can be taken to be directed toward other users. Lines beginning with three asterisks are system messages representing changes in the state of the channel what participants are on, who the operators are, etc. Since only participant turns and actions are the focus of the linguistic interaction, these lines were separated for subsequent analysis.
System messages and commands were collected in a separate database for tracking participant identities. the nick in angle brackets, or the nick following the initial asterisk. These nicks were then located in the database of system messages to be matched with a participant identity.
A similar analysis of addressees was also conducted. Often a speaker identifies the addressee directly in a turn or action [ 20 ]; if they do not, then often the addressee of a turn or action can be identified by reading the log. When an addressee was identified in either of these ways, the system message database was again consulted to establish the identity of the addressee by matching the appropriate nick with an e-mail identity.
All told, lines of participant turns and actions were identified. In a positional analysis, participants are grouped in more or less equivalence classes, according to their patterns of interaction with other participants. Frequencies of interaction among all the pairs of participants were tabulated by sorting the database records by speaker and addressee, and arranging the table so that speakers were listed in the rows of the table, and addressees were listed in the columns, resulting in a speaker by addressee directional matrix [ 18, 19 ].
Such a large table, of course, is very sparse, containing mostly zeros in its cells, since most people will never converse with one another.
This necessitated that two smaller matrices be constructed from the first; one a 92 by matrix where the 92 most frequent participants are speakers, the other being a 92 by matrix where they are addressees. The two tables thus represent non-identical but overlapping sets of data, the combination of which represents the total interactional behavior of the 92 most frequent participants on the channel, the strength of absent ties social integration via online dating.
Structurally equivalent participants in each table were then identified using factor analysis [ 7, 8, 16, 18 ]; from the first table, the 92 participants would be grouped according to their patterns of shared behavior as speakers, and from the second table they would be grouped according to their shared patterns of behavior as addressees.
[v2] The Strength of Absent Ties: Social Integration via Online Dating
OAI identifier: oai:blogger.com:publications/a8bbfcdeabccadf7ec7 · With respect to tie strength, only Hindi use is localized among the network's strongest ties, while the other features are localized in areas of weaker tie strength. Social Network Analysis The two factor analyses produced four-factor solutions, as determined by a scree-test [ 7, 16 ] · However, online dating has changed this pattern; people who meet online tend to be complete strangers. We investigate the effects of those previously absent ties on the diversity of modern societies. We find that social integration occurs rapidly when a society benefits from new connections
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