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Lecture 5

Lecture 5 Oct 12 Lecture.docx

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Department
Sociology
Course
SOC355H1
Professor
Alexandra Marin
Semester
Fall

Description
SOC355Y1 Tuesday October 12, 2010 Last week you learned: - Creating a new field required building bridges between previously unconnected scholars, creating a cluster of scholars in conversation with other another - There are lots of different kinds of networks Today’s outline: - Which nodes? Which relations? Which measures? - Collecting network data o Observation o Archives o Surveys/interviews 1. Rosters 2. Name generators and interpreters 3. Position generators 4. Resources generators - Where do you get data? Social network data is different from other data. This is because sociologists collect some attribute data, but network analysts want relations, connections! - Think about where the data comes from… a lot of sociologists try to be objective – therefore sociologists collect social network data by observing, who is in a relationship… Advantages: o In theory it is more objective: you can train an observer what constitutes a relation. o Eliminates bias in memory which respondents usually have o Differences in how people interpret data - Most data is not based on observations though, in social networking, because it is hard to obtain, expensive, impractical for a lot of relations, and even when we observe things (relations you can observe) networks do not exist. Networks not existing mean friendship relations do not exist in the form drawn in a sociogram for example. Essentially you are not enacting the relationship in the way it is drawn, all connected at once. What it means is that at any given moment you may be engaging in a behaviour associated with a relationship but these relationships do not exist all simultaneously the way we draw and think about them. This matters because when we enact a relationship (ex. Call our friends, talk to people we like, work with someone) all those things we observe are affected by the relationship surely (you call a friend because they are your friends) but it is also enacted by a set of rules (ex. Not calling friends in class) – we all live in a context where observations can be enacted via rules. It may be about a rule, if we see there is no relation it may be that it is no being enacted or that a rule is being enacted. - Ex: wedding in a park is not a network because there are clusters that talk proportionately to everyone; there are some that talk to everyone, and some that talk to almost everyone. You could say these people have strong relations with everyone and some who have strong relations to couple but not all others. Therefore when you go to a wedding, you are seated at a table, you do not get to choose who you would like to talk to, you simply talk to people at table – rules of interaction – couple will talk to everyone at the wedding, this is decided by rules that govern when interactions are made. Therefore you must understand what you are observing, something created by rules? Or something by relation? - David Gibson example – observed people at bank, collecting underlying observation data, looked at who they talked to and how it was enacted- people who are not friends do talk at meetings, you can still infer friendships at a business meeting however… disproportionate interaction: one person talks, then the friend gives an excuse for the other- even if you do not know content of conversation, rather “form”, you can spot the relationship or friendship! - Next step: Archival data! o Find records of relations o Ex: marriage records, God parent records from church archives, Facebook is an example or archive, alliance between companies, citations are archives o The advantage: in theory it is easy to collect o Disadvantages: 1. for a lot of ties archival data does not really exist (there are letters though but usually it does not exist), 2. the data are created for other purposes and not social network analysts therefore not rigorous in the way you need it to be, people may not mean what they portray in data, and for older archives they tend to be incomplete. - A lot of data collected by network analysts is survey data! - Network survey- if you want to do a survey of a whole-network (bird’s eye view, set of nodes and connections between them) the problem with collecting whole network surveys is deciding who exactly is in the nodes? – decide who is in and who is out? In considering a node: how? o From Scott book: 1. Take a positional based approach. Therefore choose positions- ex. “vice president of organization, top two in charge” – Ex: list of jobs, whoever is in them, those are the nodes 2. Take an event based approach. Ex: “I want to study social network analysts, and to decide who is a social network analysts whoever has been to at least 2 out of 5 Sunbelt conference, is going to be used therefore is considered a node. Going to be in the list of nodes. 3. Relational based approach- takes a few people you are sure are in the network, then you ask a question where you want referred or mentioned individuals- similar to snow-ball approach. o Now list of people in network! So to study the network: 1. Ideal way- Use a roster! – This is a type of survey question, a roster is a list of nodes, you ask each respondent who they share a relation with. - Keith Hampton of Boston did E-neighbour survey – he gave everyone access to a website where they could talk to neighbours, mailing list, and looked at neighbourhoods before access to internet and then after access to internet. – Ex: he asked respondents if they recognized another’s name, how they contacted that person or came into contact with that person (used binary data, recognized them or not) – Once everyone answered you could make a directed matrix. - Rosters have a huge advantage- no one forgets someone in a roster! Unless someone does not read the roster, for example when there are too many names! - Disadvantage: Rosters – you do not know the names of who would be on the roster- or at least should be on the roster- but if it is a small group, and you have access to a group of people who would be on the list, a roster is nice 2. Name generator – used for both ego and whole networks- it is a survey question asking people to list people who they have interactions with “Ex: who are the people you discuss important matters with?” – Usually when you ask this question you want a list of names HOWEVER we must worry about Ethics- ethics worry about you being surveyed but information collected about others as well – to alleviate these concerns, we assure respondents we will not contact these people, and secondly we just ask for a first name or initials, we ask for other names so respondents can know who person is, name generators are followed by name interpreters - When we are interested in social support we usually have more than one name generator - Ex: “List anyone important to you who you have not already listed” Example from E-Neighbour survey - Name interpreters, surv
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