So I've finally finished analyzing all the data from the sociolinguistics experiment you helped me with. The essay's not done; I've just finished the graphs, correlations, explanations, etc.
Are you interested? Do you care? If you do, I'll post the results. If not, I won't be offended! I promise!
Here's a question for all you guys.. NSFW 18+
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[PX] Nebuchadnezzar
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THE JEW (RaVeN)
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Minus some detail and not yet edited....
Density
Density is a measure of the links between a group. A network is said to be dense if many of the members are linked to each other. The density of a network can be calculated using a simple formula expressing the ratio of the total possible links to the total number of actual links in the network:
Density = number of actual links / number of possible links
= 8 / 28
= 28.57%
Networks that are relatively dense are usually considered to function effectively as norm enforcement mechanisms. This means that the denseness of these networks can enhance and expand the use of language or slang as their own personal vernacular.
• Clusters
Segments of networks with high density are called clusters. Most people’s personal networks consist of series of clusters; relationships within these clusters are generally denser than the relationships that exist outside of the cluster. Generally, these relationships are of “like content”. (Milroy, 50) In this group, the “like content” centers around computers, computer games, video games, and the like.
Multiplexity
Multiplexity is a measure of the multiplex, or multiple, links within a network. The links that were used in the density measurement may have been uniplex (a single relationship) or multiplex (more than one relationship). For example, the same people may be connected as roommates and as co-workers. The multiplexity score for an individual can be calculated as a ratio of multiplex ties to all actual links:
Multiplexity = number of multiplex links / number of actual links (Milroy, 51)
(links observed: living together ; working together ; gaming together)
*pretend there's a chart with the multiplexity scores here*
- The problem with this sort of measure is that they may vary from one observer to another, depending on the links they choose to observe.
- A high multiplexity score will increase the effectiveness of the network maintaining its personal vernacular.
- A network having a high density and having high multiplexity links will have the best chance of effective norm-enhancing. They normally co-occur. (Milroy, 52)
Network Score
A network score measures the network patterns between members of the group, and the pressures that are put upon a member to assume the norms (linguistic and otherwise) of the group. This is determined by using a network strength scale. This measure consists of a scale going from 0 to 5. This scale takes references from multiplexity and density, using several of the indicators for these measures for the network score. The individual network score is calculated by assigning each person with one point for each of the criteria they fulfill:
Criteria
1. Membership of a high density, territorially based cluster*
2. Working (or have worked) at the same place as at least one other from the group*
3. Talk with at least one other at least 5 times a week
4. Play online/video game with one other at least 3 times a week
5. Live with (or have lived with in the last 5 years) at least one other
* Are from original criteria (Milroy, 141-142)
Criteria one is an indicator of density, while criteria two through five are indicators of multiplexity. Though this is not the criteria used by Milroy in her study, she states that “an entirely different set of criteria for measuring network structure might, with equal validity, have been chosen.” (Milroy, 143) Thus, these criteria have been chosen to fit the group studied, as well as indicate the multiplexity of their relationships, as demonstrated by the scatterplot below. (Omitted) Because the individual network score rises as the individual multiplexity rises, this shows that the criteria used was a good fit to the network.
*pretend theres a chart with network scores here*
Language Score
The language score is a measurement of the relevant language used by the informant. In this instance, slang promoting solidarity was studied. When any informant used language in any way that was understood by the group, but most likely not by members outside the group, one point was allotted. For every instance where any informant did not understand language used by the rest of the group, one point was deducted. These points are subjective in allocation.
- See transcription for allotment of points
*chart with Language scores here*
Two Part Analysis
1. Quantitative Analysis
Bar graph: In general, as the mean length of friendship increases, so do the individual language scores.
Scatterplot: There is a strong, positive linear relationship, indicating that as the mean length of friendships increases, so does the language score
Hypothesis: The language becomes more specialized as the friendships grow. As more time is spent as a member of the group, each individual becomes more exposed to the group vernacular, perhaps even contributing to it.
Bar Graph: There is almost a bell shaped pattern to the bar heights.
Scatterplot: There is a weak, positive, linear relationship, indicating a correlation between a rising language score and a rising length of friendship.
- However, at a length of 16-17 years, the points branch out. It begins to take on an “arrow” shape.
Hypothesis: This could demonstrate the beginning of a gradual phasing out of this particular social network. The new friendships (10 -13 years) have lower language scores, indicating their newness to the group and the group vernacular. The older friendships (18 years) also have lower language scores. This could be because, as the members of the group age, they begin to expand their networks and become part of other groups. Thus, their ties to the core network would begin to diminish, and they would not be exposed to the group vernacular as often. The mid-length friendships (15-17 years) have the largest language scores as these members are firmly established in their friendships and are fluent in the group vernacular.
Multiplexity and Network Score
Correlation
Coefficient .895
Sig. (1-tailed) .001
- There is a correlation between network score and the multiplexity with in the group, significant at the 0.01 level. This means that, if this study was reproduced 100 times, there would be a correlation between these two factors 99 of those times.
- This correlation is 0.895. A perfect correlation would be 1.0. Thus, since the correlation here is almost 0.9, this is a very strong correlation.
- All of this means that each individual network score is strongly and directly dependent on the multiplexity within the group. This is important, as it means that the criteria used to calculate the network score was good.
- As well, this means that as the links between the members of the group increase (the multiplexity), so do the pressures that are forcing them to adopt the same linguistic features as the rest of the group (the network score).
Language Score and Mean Length of Friendships
Correlation
Coefficient .861
Sig. (1-tailed) .003
- There is a correlation between language score and the mean length of friendships with in the group, significant at the 0.01 level. This means that, if this study was reproduced 100 times, there would be a correlation between these two factors 99 of those times.
- This correlation is 0.861.A perfect correlation would be 1.0. Thus, since the correlation here is almost 0.9, this is a very strong correlation.
- All of this means that each individual language score is strongly and directly dependent on the mean lengths of friendships within the group. The longer that an individual has been a member of the group (the mean length), the more likely they are to use the slang that is promoted by the group (the language score).
2. Qualitative Analysis
Exchange Theory
This group makes up a first order network zone; they are linked directly to each other. One of the purposes of a social network is to exchange goods and services, to impose obligations and bestow communication rights upon its members. This is known as the exchange theory. Used by Kapferer and Boissevan, this theory explains how people act in order to maintain important social relationships (Milroy, 47) “Messages which pass along network links can be seen as transactions, governed by the principle that the value gained by an individual in a transaction is equal to, or greater than, the cost.” (Milroy, 47-8 ) These transactions may be greetings, civilities, jokes, information, etc (Milroy, 48 ) In fact, most speech events are items of exchange.
The idea of obligation goes along with the exchange theory. Sometimes more valuable exchanges are provided by one person than another. They may be more valuable because of the desire for a certain type of personality, leadership ability, ability to tell jokes, etc. This creates an obligation to return them such valuable exchanges. Because of this asymmetry and sense of obligation, the network becomes a “mechanism” in which a certain pressure is felt, which can influence an individual’s behaviour towards the norms of the group. (Milroy, 49) This is noticed in the shared vernacular of the group studied here. In an effort seen universally to “fit in” and become more common and like the other members of the group, a similar, non-standard vernacular is used by all of the members of this close-knit group.
John Gumperz: Network Concept
John Gumperz makes a two-way distinction between “open” and “closed” network types. Closed networks refer to the relatively dense and multiplex networks, while open networks refer to the relatively sparse and uniplex networks. (Milroy, 168) The members of the group studied here clearly form a closed network, consisting of many multiplex links. The members work together, live together, socialize together and play computer/video games together.
According to Gumperz, individuals who interact mainly within closed networks share many “communicative preferences […] of a non-standard kind.” (Milroy, 168) This is the case with the group studied here, who use many terms coined from video and computer games not known by the general public. As well, their speech contains many references to private jokes and stories known by the group. These references do not explain the stories or jokes, and thus the meanings are dependent on being a member of this group. This is part of being within the closed network, according to Gumperz. He asserts that “outsiders generally do not have access to [the specialized] meanings” of the non-standard vernacular. (Milroy, 169)
Also, according to Gumperz’s theory, dense, close-knit networks function as important instruments in maintaining a specialized vernacular. Thus, the closer a network of people is, the more likely they are to sustain such slang. In the group studied here, the members who have been in contact the longest are more cognizant of the specialized language and make use of that language much more frequently. This in turn stands to demonstrate the strength of their membership within the group.
Also, you're all giant dorks.
Density
Density is a measure of the links between a group. A network is said to be dense if many of the members are linked to each other. The density of a network can be calculated using a simple formula expressing the ratio of the total possible links to the total number of actual links in the network:
Density = number of actual links / number of possible links
= 8 / 28
= 28.57%
Networks that are relatively dense are usually considered to function effectively as norm enforcement mechanisms. This means that the denseness of these networks can enhance and expand the use of language or slang as their own personal vernacular.
• Clusters
Segments of networks with high density are called clusters. Most people’s personal networks consist of series of clusters; relationships within these clusters are generally denser than the relationships that exist outside of the cluster. Generally, these relationships are of “like content”. (Milroy, 50) In this group, the “like content” centers around computers, computer games, video games, and the like.
Multiplexity
Multiplexity is a measure of the multiplex, or multiple, links within a network. The links that were used in the density measurement may have been uniplex (a single relationship) or multiplex (more than one relationship). For example, the same people may be connected as roommates and as co-workers. The multiplexity score for an individual can be calculated as a ratio of multiplex ties to all actual links:
Multiplexity = number of multiplex links / number of actual links (Milroy, 51)
(links observed: living together ; working together ; gaming together)
*pretend there's a chart with the multiplexity scores here*
- The problem with this sort of measure is that they may vary from one observer to another, depending on the links they choose to observe.
- A high multiplexity score will increase the effectiveness of the network maintaining its personal vernacular.
- A network having a high density and having high multiplexity links will have the best chance of effective norm-enhancing. They normally co-occur. (Milroy, 52)
Network Score
A network score measures the network patterns between members of the group, and the pressures that are put upon a member to assume the norms (linguistic and otherwise) of the group. This is determined by using a network strength scale. This measure consists of a scale going from 0 to 5. This scale takes references from multiplexity and density, using several of the indicators for these measures for the network score. The individual network score is calculated by assigning each person with one point for each of the criteria they fulfill:
Criteria
1. Membership of a high density, territorially based cluster*
2. Working (or have worked) at the same place as at least one other from the group*
3. Talk with at least one other at least 5 times a week
4. Play online/video game with one other at least 3 times a week
5. Live with (or have lived with in the last 5 years) at least one other
* Are from original criteria (Milroy, 141-142)
Criteria one is an indicator of density, while criteria two through five are indicators of multiplexity. Though this is not the criteria used by Milroy in her study, she states that “an entirely different set of criteria for measuring network structure might, with equal validity, have been chosen.” (Milroy, 143) Thus, these criteria have been chosen to fit the group studied, as well as indicate the multiplexity of their relationships, as demonstrated by the scatterplot below. (Omitted) Because the individual network score rises as the individual multiplexity rises, this shows that the criteria used was a good fit to the network.
*pretend theres a chart with network scores here*
Language Score
The language score is a measurement of the relevant language used by the informant. In this instance, slang promoting solidarity was studied. When any informant used language in any way that was understood by the group, but most likely not by members outside the group, one point was allotted. For every instance where any informant did not understand language used by the rest of the group, one point was deducted. These points are subjective in allocation.
- See transcription for allotment of points
*chart with Language scores here*
Two Part Analysis
1. Quantitative Analysis
Bar graph: In general, as the mean length of friendship increases, so do the individual language scores.
Scatterplot: There is a strong, positive linear relationship, indicating that as the mean length of friendships increases, so does the language score
Hypothesis: The language becomes more specialized as the friendships grow. As more time is spent as a member of the group, each individual becomes more exposed to the group vernacular, perhaps even contributing to it.
Bar Graph: There is almost a bell shaped pattern to the bar heights.
Scatterplot: There is a weak, positive, linear relationship, indicating a correlation between a rising language score and a rising length of friendship.
- However, at a length of 16-17 years, the points branch out. It begins to take on an “arrow” shape.
Hypothesis: This could demonstrate the beginning of a gradual phasing out of this particular social network. The new friendships (10 -13 years) have lower language scores, indicating their newness to the group and the group vernacular. The older friendships (18 years) also have lower language scores. This could be because, as the members of the group age, they begin to expand their networks and become part of other groups. Thus, their ties to the core network would begin to diminish, and they would not be exposed to the group vernacular as often. The mid-length friendships (15-17 years) have the largest language scores as these members are firmly established in their friendships and are fluent in the group vernacular.
Multiplexity and Network Score
Correlation
Coefficient .895
Sig. (1-tailed) .001
- There is a correlation between network score and the multiplexity with in the group, significant at the 0.01 level. This means that, if this study was reproduced 100 times, there would be a correlation between these two factors 99 of those times.
- This correlation is 0.895. A perfect correlation would be 1.0. Thus, since the correlation here is almost 0.9, this is a very strong correlation.
- All of this means that each individual network score is strongly and directly dependent on the multiplexity within the group. This is important, as it means that the criteria used to calculate the network score was good.
- As well, this means that as the links between the members of the group increase (the multiplexity), so do the pressures that are forcing them to adopt the same linguistic features as the rest of the group (the network score).
Language Score and Mean Length of Friendships
Correlation
Coefficient .861
Sig. (1-tailed) .003
- There is a correlation between language score and the mean length of friendships with in the group, significant at the 0.01 level. This means that, if this study was reproduced 100 times, there would be a correlation between these two factors 99 of those times.
- This correlation is 0.861.A perfect correlation would be 1.0. Thus, since the correlation here is almost 0.9, this is a very strong correlation.
- All of this means that each individual language score is strongly and directly dependent on the mean lengths of friendships within the group. The longer that an individual has been a member of the group (the mean length), the more likely they are to use the slang that is promoted by the group (the language score).
2. Qualitative Analysis
Exchange Theory
This group makes up a first order network zone; they are linked directly to each other. One of the purposes of a social network is to exchange goods and services, to impose obligations and bestow communication rights upon its members. This is known as the exchange theory. Used by Kapferer and Boissevan, this theory explains how people act in order to maintain important social relationships (Milroy, 47) “Messages which pass along network links can be seen as transactions, governed by the principle that the value gained by an individual in a transaction is equal to, or greater than, the cost.” (Milroy, 47-8 ) These transactions may be greetings, civilities, jokes, information, etc (Milroy, 48 ) In fact, most speech events are items of exchange.
The idea of obligation goes along with the exchange theory. Sometimes more valuable exchanges are provided by one person than another. They may be more valuable because of the desire for a certain type of personality, leadership ability, ability to tell jokes, etc. This creates an obligation to return them such valuable exchanges. Because of this asymmetry and sense of obligation, the network becomes a “mechanism” in which a certain pressure is felt, which can influence an individual’s behaviour towards the norms of the group. (Milroy, 49) This is noticed in the shared vernacular of the group studied here. In an effort seen universally to “fit in” and become more common and like the other members of the group, a similar, non-standard vernacular is used by all of the members of this close-knit group.
John Gumperz: Network Concept
John Gumperz makes a two-way distinction between “open” and “closed” network types. Closed networks refer to the relatively dense and multiplex networks, while open networks refer to the relatively sparse and uniplex networks. (Milroy, 168) The members of the group studied here clearly form a closed network, consisting of many multiplex links. The members work together, live together, socialize together and play computer/video games together.
According to Gumperz, individuals who interact mainly within closed networks share many “communicative preferences […] of a non-standard kind.” (Milroy, 168) This is the case with the group studied here, who use many terms coined from video and computer games not known by the general public. As well, their speech contains many references to private jokes and stories known by the group. These references do not explain the stories or jokes, and thus the meanings are dependent on being a member of this group. This is part of being within the closed network, according to Gumperz. He asserts that “outsiders generally do not have access to [the specialized] meanings” of the non-standard vernacular. (Milroy, 169)
Also, according to Gumperz’s theory, dense, close-knit networks function as important instruments in maintaining a specialized vernacular. Thus, the closer a network of people is, the more likely they are to sustain such slang. In the group studied here, the members who have been in contact the longest are more cognizant of the specialized language and make use of that language much more frequently. This in turn stands to demonstrate the strength of their membership within the group.
Also, you're all giant dorks.
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THE JEW (RaVeN)
- Posts: 12499
- Joined: Sun Mar 23, 2003 2:52 pm
- Location: Bethlehem ;)
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If you typed all that..........bravo.
The easiest way, most likely, to get the graphs would be to scan them and then upload them to your album. Then just post the pics within the post.
Dorks..............giving black rappers a run for their money in the slang department.
The easiest way, most likely, to get the graphs would be to scan them and then upload them to your album. Then just post the pics within the post.
Dorks..............giving black rappers a run for their money in the slang department.
******* /=========\
****(_]/_____________\[_)
***** /(__)==JEW==(__)\
***** |=o__________o=|
***** |_|====---====|_|
¨˜”°º•[K]•º°”˜¨
****(_]/_____________\[_)
***** /(__)==JEW==(__)\
***** |=o__________o=|
***** |_|====---====|_|
¨˜”°º•[K]•º°”˜¨
-
Ghost [PX]
- Posts: 3392
- Joined: Sun Mar 23, 2003 2:36 am
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THE JEW (RaVeN) wrote:Dorks..............giving black rappers a run for their money in the slang department.
LOL!
Nature is bountiful where idiots are concerned
No, they arent breasts, they're personalities, because its ok to like a girl for her personalities
It takes a big man to cry, but it takes a bigger man to laugh at that man
No, they arent breasts, they're personalities, because its ok to like a girl for her personalities
It takes a big man to cry, but it takes a bigger man to laugh at that man
THE JEW (RaVeN) wrote:If you typed all that..........bravo.
The easiest way, most likely, to get the graphs would be to scan them and then upload them to your album. Then just post the pics within the post.
Graphs are up now
and I just copied and pasted my assignment. Don't worry, you guys aren't special enough for me to type all that out for nothing
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THE JEW (RaVeN)
- Posts: 12499
- Joined: Sun Mar 23, 2003 2:52 pm
- Location: Bethlehem ;)
- Contact:
Here, try hosting the graphs here:
http://kalnet.kalshadowtech.com/php/phpBB2/album.php
Click on the link that says "Your Personal Gallery." Anyone who signs up at Kalnet has access to it. It'll allow you to host larger pictures. All the giant pictures of man@$$ I post.....get hosted there
http://kalnet.kalshadowtech.com/php/phpBB2/album.php
Click on the link that says "Your Personal Gallery." Anyone who signs up at Kalnet has access to it. It'll allow you to host larger pictures. All the giant pictures of man@$$ I post.....get hosted there
******* /=========\
****(_]/_____________\[_)
***** /(__)==JEW==(__)\
***** |=o__________o=|
***** |_|====---====|_|
¨˜”°º•[K]•º°”˜¨
****(_]/_____________\[_)
***** /(__)==JEW==(__)\
***** |=o__________o=|
***** |_|====---====|_|
¨˜”°º•[K]•º°”˜¨