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NC_for_Social_Network_Data_collection.qmd
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---
title: "Data collection Instruments for Egocentric Networks"
subtitle: "EPH 647: Community Based Participatory Research and Social Network Analysis"
author: "Ana Bravo"
date: now
format:
revealjs:
theme: simple
scrollable: true
slide-number: true
css: light.css
editor: source
---
## Objectives
- Understand Ego-centric data and the different data types.
- To understand the different major components of ego-centric (personal network) data.
- To understand the different types of data collection instruments (focus Network Canvas)
- Understand the major features and components of Network Canvas.
- Live demonstration of a Network Canvas Social Network protocol.
# Ego-centric Data 🙆♂️
## Ego-centric Data Types
- Ego-centric *(also called personal network)* data, typically has three main data types:
::: panel-tabset
### Ego-level data
Data about the respondent *(called ego)*. which consists of each row as the participant/ego response, and each column represents a variable or characteristic of the ego (e.g., egos age, BMI, smoking status, etc.)
{fig-align="center" width="552"}
### Alter-level data
Which consist of the egos nominated *alters* (e.g, peers, friends, etc.) characteristics (e.g., alter age, ethnicity, etc.) and *ego-alter dynamics* (e.g., closeness to alter, frequency of meeting, shared a meal together etc.)
{fig-align="center" width="540"}
### Alter-alter data
Data that includes the alter-alter ties as reported by ego. This is also called an *“edge list”* or can be described as an adjacency matrix. For example:
- alter 1 and alter 2 know each other.
- alter 1 and alter 2 meet when ego is not there.
- alter 1 and alter 2 have shared a meal together.
{fig-align="center" width="259"}
:::
::: {style="font-size:15px"}
# *In ego-centric (also called personal networks) data, alters can only belong to one ego, and alter-alter ties only exist between alters that were nominated by the same ego. In other words, in this type of analysis, there is no overlap between the different networks of different egos.*
```{r}
library(igraphdata)
library(ggraph)
library(patchwork)
library(graphlayouts)
data("karate")
p1 <- ggraph(karate, layout = "focus", focus = 1) +
draw_circle(use = "focus", max.circle = 3) +
geom_edge_link0(edge_color = "black", edge_width = 0.3) +
geom_node_point(aes(fill = as.factor(Faction)), size = 2, shape = 21) +
scale_fill_manual(values = c("#8B2323", "#EEAD0E")) +
theme_graph() +
theme(legend.position = "none") +
coord_fixed() +
labs(title = " Ego Network UM1010")
p2 <- ggraph(karate, layout = "focus", focus = 34) +
draw_circle(use = "focus", max.circle = 4) +
geom_edge_link0(edge_color = "black", edge_width = 0.3) +
geom_node_point(aes(fill = as.factor(Faction)), size = 2, shape = 21) +
scale_fill_manual(values = c("#8B2323", "#EEAD0E")) +
theme_graph() +
theme(legend.position = "none") +
coord_fixed() +
labs(title = "Ego Network UM1034")
# Patch work
p1 + p2
```
:::
# Data Collection Methods 👩💻
## Data Collection Software
- Social network analysis (SNA) is a growing field and there are many different data collection software, which you can check out a list of different data collect software [here.](https://raffaelevacca.github.io/Open-social-network-surveys/)
- However, for today we will focus on [Network Canvas.](https://networkcanvas.com/)
{fig-align="center"}
## What is Network Canvas
Network Canvas (NC) is a data collection software, specifically tailored to handle *social network data*. It has different capability to support the major components of personal network projects as well as the flexibility to adapt to different study designs.
- It is free and open source.
- It is intuitive and user friendly.
- Their development community is open to feedback and suggestions.
- you also can communicate with their development team through their [community forums.](https://community.networkcanvas.com/)
- It works well with major data wrangling software, like Python and R.
## Major Components of Network Canvas
Network Canvas has three main programs:
::: panel-tabset
### Architect
which is the software that allows primary investigators and researchers the ability to *build* their Social Network protocol. (e.g., this is where the researcher can define the different *data types* and the different questions)
{fig-align="center" width="503"}
### Interviewer
which is the software that helps *deploy and run* the network canvas interview. (e.g., This is where the research assistant and the participant complete the questionnaires)
{fig-align="center" width="544"}
### Server
The central hub software to keep multiple network canvas protocols updated if you are running a major, multi-site study.
- The Network Canvas (NC) team is expecting to launch a *“studio”* version, to be able to support for longitudinal project designs in about 2-3 years, so this software workflow may change.
- For this lesson, we will not be talking about server today, as the typical way for social network researchers to *use* Network Canvas is through the architect and interviewer software.
{fig-align="center" width="460"}
:::
# Personal Network Data Collection Fundamentals 🧑🤝🧑
## Components of Personal Network Research
::: {style="font-size:29px"}
- When collecting personal network data, there is a few fundamental principles that researchers are interested in collecting when running SN projects:
- The way that network canvas is structured, it tried to capture social network data in its most *fundamental* way, by capturing **nodes** and **edge** attributes. To collect this type of data, there are *generally* 4 main components needed:
:::
::: panel-tabset
### Ego Form
- A survey that can collect ego characteristics, such as, age, BMI, smoking status, etc.)
- This type of data can be collected via NC, but it can also be collected through other survey software. My favorite, in my opinion the golden standard, is \[REDCap.\](<https://www.project-redcap.org/>)
- Keep in mind that REDCap does **not** really support network data like NC does, but it is great when you're interested in collecting ego data.
- for example: mental health scales like MACVS, PTSD scales, demographic information.
{fig-align="center" width="545"}
### Names
also called *Name Generator*:
- NC ability to produce alters, that the ego can nominate in their personal network.
- This allows for building out the personal networks. There are different name generator form types (depending on your data needs), such as quick add per network, quick add per alter, using roasters for recall etc.)
- *For example: "Think about the people you know: Who are the people in which you discuss personal matters with? List up to 13 individuals."*
{fig-align="center" width="551"}
### Alter-ego
Also called *Alter Ego Attributes*:
- NC ability to capture alter-ego *dynamics.* (e.g., closeness, frequency of contact, etc.)
- This is also where the researcher has the ability to capture ordinal categorical type of data. (e.g., how close is the ego to the alter? Very close, somewhat close, not close at all)
{fig-align="center" width="545"}
### Socio-gram
- This allows for the participant and researcher, to describe and *build* the *layout* of their personal networks.
- NC allows for different types alter-alter tie connections.
- For example, the tie between two alters represents that the alters "know" each other, or "hang out" together when the ego is not there, or "have fought" with each other.
- A *sociogram* is one type of method to building personal networks, but there are other types that are supported by network canvas, such as dyad-census (which goes through every possible dyad connection to build the ties)
{fig-align="center" width="522"}
{fig-align="center" width="512"}
:::
# Possible Research Questions 👨🔬
## Questions to consider when building a protocol
- This largely depends on your research of interest; however, you can collect different alter attributes, such as, egos perception of their alters age, emotional closeness to alter, etc.
- NC is very flexible and can *almost* support any type of question of interest.
- Additionally, when building a network protocol, there needs to be some forethought about the *type* of data you might want to collect. For example:
- What are some of the data types you are expecting to collect? (e.g., ordinal, categorical, text)
- What *input controls* (more on that later) would be best to use to visualize the protocol?
- You can ask questions like:
- contact frequency
- perceived age
- disclosure of HIV status
- likelihood to talk about PrEP in the next 6 months
## Input control
*Input control* is the ability to modify the way in which the data is presented and how it will collected.
- For example, you can use a calendar type input control for age, or a text field for name.
{fig-align="center" width="570"}
## Variable Types
- When collecting data, really in any human subject research, considering the type of data you are collecting is important.
- Network Canvas has support for many types of variables:
- **Text** Basic short text string,
- **Number** Basic whole number (integer),
- **Ordinal** Ordered categorical data, where each value is described by a label and a value. Only supports single values,
- **Categorical** Unordered categorical data where each value is described by a label and a value. Supports multiple values.
- **Boolean** True or False values,
- **Layout** X/Y coordinate values, normalized between 0 and 1 in each axis.
- **DateTime** Date variable capable of storing resolution down to the day.
- **Scalar** A continuous floating point number between 0 and 1
## Edge Types
- In personal network research, edges describe the relationship between alters.
- Network Canvas supports different edge types, which can be used to capture different types of relationships between alters.
{fig-align="center"}
# Recommended Social Network Project Building Process 🏗
## Recommendations for creating a protocol
Typical creation of a network canvas protocol is:
- create a Stage based on whether you are collecting Ego, Node, or Edge data.
- Include a stage name (e.g., Ego Form, Name Generator, etc.)
- Create a name generator to collect alter data.
- Create variables.
- Add a prompt (or a script) for that variable.
- Select an input control (calendar, text field, etc.)
You can check out the Network Canvas recommended protocol building workflow [here.](https://documentation.networkcanvas.com/tutorials/building-a-protocol/)
## Burden Reduction
- In all human subject research (HSR), especially in epidemiological designs with complicated protocols, there’s always a give-and-take regarding burden level.
- This is something to always keep in mind when conducting HSR, and therefore important to implement tips in any protocol workflow.
- Tactics to reduce protocol burden includes skip logic:
::: {.column width="100%"}
{fig-align="center" width="700"}
:::
## General Protocol Process Workflow 🔄
Generally, when running the protocol with a potential participant, the process would look something like this:
::: {.column width="100%"}
{fig-align="center" width="692"}
:::
## Resources
- There are many great resources for collecting sound protocol measures using NC, one of them being directly from the NC team:
- [Conducting Personal Network Research with Network Canvas](https://www.youtube.com/watch?v=3EZAnB9_-cA)
- [Working with Network Canvas data in R](https://documentation.networkcanvas.com/tutorials/working-with-data/)
- And others resource from Social network scientists:
- [Ego Centric Network Analysis with R](https://raffaelevacca.github.io/egocentric-r-book/index.html)
- [Network Visualization using R](http://talks.schochastics.net/netVizR/slides.html#1)
## A Network Canvas Protocol Example
*A two mode approach*
::: {style="font-size:30px"}
- We are going to be looking at a Network Canvas Protocol example that was built for the `LatiNET` study.
- `LatiNET` is a multi-level study using a social network approach to examine how COVID-19 misinformation and conspiracy theories impact Latino vaccine hesitancy across 5 domains:
- Friends
- Family
- Work
- Health Services
- Influences
- `LatiNET` covers the social network project fundamentals, like name generators, and questionnaires regarding the relationships with nominated alters.
- Personal network data typically measures data at the “micro-level” (e.g., between dyads), and with these relationships, we are able to make inferences about about these relationships at the “macro-level”
- A *two-mode* approach, describes ties between two nodes at different levels of analysis. In other words, affiliation or relationship to structures. So nodes/egos affiliation to their macro structure (in the `LatiNET` case, health services, influences (e.g., political, social etc.) and community channels.
- A two mode approach helps researchers understand the macro-micro dynamics and help control for societal structures that impact observed relationships, like structural racism.
- in the `LatiNET` study, a two-mode approach helps us understand how egos affiliation or relationship with different media outlets may impact their relationship with vaccines.
- This is the idea of network data, in which individuals are "nested" *within* larger structures, and those larger structures are nester *within* even larger structures.
:::
# Live Demo 🧑🔧
## Overview
Today you learned:
- The basics of personal network data types.
- Data collection methods in personal network research.
- A gentle introduction on how to build a NC protocol.
- Different components of the Network Canvas software.
- Recommended workflow for build a social network protocol.
## References and Acknowledgements 📚
- [Network Canvas Team Resources](https://documentation.networkcanvas.com/tutorials/building-a-protocol/)
- [Ego Centric Network Analysis with R](https://raffaelevacca.github.io/egocentric-r-book/)
- [Network Visualization in R: Using ggraph and graphlayouts](http://talks.schochastics.net/netVizR/slides.html#1)
- [ggraph: A grammar of graphics for relational data](https://ggraph.data-imaginist.com/)
- [R4SNA](https://schochastics.github.io/R4SNA/descriptives-basic.html)
- [Egocentric Network Analysis: Foundations, Methods, and Models](Egocentric%20Network%20Analysis:%20Foundations,%20Methods,%20and%20Models)
- [Conducting Personal Network Research: A Practical Guide](https://www.amazon.com/Conducting-Personal-Network-Research-Methodology/dp/146253838X/ref=asc_df_146253838X/?tag=hyprod-20&linkCode=df0&hvadid=333955095017&hvpos=&hvnetw=g&hvrand=804285928416711888&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9011913&hvtargid=pla-680457968138&psc=1&mcid=4d4405c4a53e3894beb8085ea15a6e0a&tag=&ref=&adgrpid=64524924422&hvpone=&hvptwo=&hvadid=333955095017&hvpos=&hvnetw=g&hvrand=804285928416711888&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9011913&hvtargid=pla-680457968138&gclid=CjwKCAjwh4-wBhB3EiwAeJsppN_cEICV242dZ3tGxrHeLfKqaZh76H-s6jmez8BJ5sAKu8wfmnTyFRoCzhEQAvD_BwE)
# Thank you! 🙏