The OpenCare Semantic Social Network Data by Kaggle | Demographics and Population Studies

About this Dataset

The OpenCare Semantic Social Network Data

Semantic OpenCare Network Analysis

Exploring Interaction Patterns and Relationship Dynamics

About this dataset

The OpenCare dataset is a unique compilation of social network data providing an in-depth look into conversations, interactions, behaviors, and relationships. It includes posts and comments from the OpenCare platform which allow users to discuss and collaborate on global health issues. With this data set you can explore annotations and coding tags used by participants to describe their discussions as well as analyze post replies, likings, and other user engagement metrics. OpenCare provides a comprehensive look at how international stakeholders interact with each other on issues related to global health — allowing policy makers, researchers, academics and even everyday citizens to gain insight on the larger implications of healthcare decisions made in different countries around the world. Join us in exploring this dataset today – there’s infinite potential when it comes uncovering trends that can improve patient care worldwide!

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How to use the dataset

Understand What’s in the Dataset- Before you can start making use of the data in this dataset, it’s important to understand what types of information are included in each column. The columns such as text contain conversation posts or comments while others include annotations or coding tags associated with particular posts or comments. It's also important to learn which columns contain unique identifiers like uri so you have an easier time working with your data afterwards.

Clean & Analyze Your Data - After exploring what is included in each column in your dataset it’s time to start cleaning it up! Depending on the type of analysis that you plan on doing you can choose which fields (columns) need to be cleaned up first before further analyzing them together such as participant’s names or post/comment contents if needed. Once these pieces are cleaned up then dive into some exploratory analytics to understand better about conversations that were held on OpenCare Platform - for example check out relationships between participants by looking into replies and likings made between different users involved in conversations etc..

Visualize Your Results- Once all your analysis has been completed its time to visualize your results so others can make sense out of it easily! Whether its using style sheets developed within a platform like Tableau or other visualization tools like ChartJS depending on what best suits the complexity levels of results/analysis one might have come across through their analysis journey! Visualizing content shared by different users who had encountered issues & collaborating attempts aimed towards crisis resolution will give an overall idea about community driven concepts being discussed using OpenCare platform

Research Ideas

Analyzing the spread of health information among different user groups to identify potential target audiences for campaigns or initiatives related to public health.

Examining relationships between users in different regions and countries based on their interactions and collaborations on openCare platform.

Visualizing the network of user relations and interactions, in order to better understand how users are connected, or have a shared interest within a particular topic related to global health issues

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: annotations.csv

Column name	Description
version	Version of the data being used. (Integer)
text	Text associated with posts or comments. (String)
quote	Quote from a post or comment if included. (String)
uri	Unique identifier for every post or comment. (String)
created_at	Date and time when each post was created by its author. (DateTime)
updated_at	Date and time when a given post was last updated by its author or anyone else who edited it afterwards. (DateTime)
type	Identifies what type of communication it is (i.e., conversation post/comment/etc). (String)
shape	Indicates the shape of the post or comment if there is one associated with it (i.e. paragraph, map, image, etc). (String)
units	Indicates what units are associated with any measurements that may be included in posts/comments (i.e. temperature, miles, hours, etc). (String)
geometry	Contains geometry information that may be associated with any posts/comments (i.e. location, latitude/longitude, etc). (String)
src	Source resource related to any references made in posts/comments. (String)
ext	Contains any additional containers associated with corresponding posts/comments. (String)
container	The start date associated with a given formation. (DateTime)
start	The end date associated with a given formation. (DateTime)

File: participants.csv

Column name	Description
Destination	If there's an identifiable intended recipient [participant] named in the communication then this field will contain their name. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Annotations

@kaggle.thedevastator_semantic_opencare_network_analysis.annotations

1.67 MB
5729 rows
21 columns


CREATE TABLE annotations (
  "id" BIGINT,
  "version" VARCHAR,
  "text" VARCHAR,
  "quote" VARCHAR,
  "uri" VARCHAR,
  "created_at" VARCHAR,
  "updated_at" VARCHAR,
  "post_id" BIGINT,
  "creator_id" BIGINT,
  "type" VARCHAR,
  "shape" VARCHAR,
  "units" VARCHAR,
  "geometry" VARCHAR,
  "src" VARCHAR,
  "ext" VARCHAR,
  "container" VARCHAR,
  "start" VARCHAR,
  "end" VARCHAR,
  "topic_id" BIGINT,
  "post_creator_id" BIGINT,
  "code_id" BIGINT
);

Codes

@kaggle.thedevastator_semantic_opencare_network_analysis.codes

120.63 KB
1384 rows
10 columns


CREATE TABLE codes (
  "id" BIGINT,
  "description" VARCHAR,
  "creator_id" BIGINT,
  "created_at" VARCHAR,
  "updated_at" VARCHAR,
  "ancestry" VARCHAR,
  "annotations_count" BIGINT,
  "name" VARCHAR,
  "name_with_path" VARCHAR,
  "names" VARCHAR
);

Participants

@kaggle.thedevastator_semantic_opencare_network_analysis.participants

5.7 KB
276 rows
3 columns


CREATE TABLE participants (
  "par" VARCHAR,
  "icipan" VARCHAR,
  "unnamed_2" VARCHAR
);

Posts

@kaggle.thedevastator_semantic_opencare_network_analysis.posts

2.93 MB
3736 rows
15 columns


CREATE TABLE posts (
  "post_number" BIGINT,
  "post_id" BIGINT,
  "created_at" VARCHAR,
  "topic_id" BIGINT,
  "reply_count" BIGINT,
  "reads" BIGINT,
  "readers_count" BIGINT,
  "incoming_link_count" BIGINT,
  "quote_count" BIGINT,
  "like_count" BIGINT,
  "score" DOUBLE,
  "reply_to_post_id" BIGINT,
  "source_username" VARCHAR,
  "target_username" VARCHAR,
  "text" VARCHAR
);