The statistic shows the revenue from online communities, a subsegment of the enterprise social network market, from 2012 to 2014, with forecasts for 2015 to 2019. In 2015, the online communities market was predicted to reach ***** million U.S. dollars in size worldwide.

As of January 2023, Instagram and Facebook were considered the most effective social media platforms for building active communities - each platform was chosen by ** percent of social media marketers surveyed worldwide. YouTube followed, with ** percent of respondents considering it effective to build an online community.

Data and code needed to reproduce the results of the paper "Effects of community management on user activity in online communities", available in draft here.

Instructions:

1. Unzip the files.
2. Start with JSON files obtained from calling platform APIs: each dataset consists of one file for posts, one for comments, one for users. In the paper we use two datasets, one referring Edgeryders, the other to Matera 2019.
3. Run them through edgesense (https://github.com/edgeryders/edgesense). Edgesense allows to set the length of the observation period. We set it to 1 week and 1 day for Edgeryders data, and to 1 day for Matera 2019 data. Edgesense stores its results in a file called JSON network.min.json, which we then rename to keep track of the data source and observation length.
4. Launch Jupyter Notebook and run the notebook provided to convert the network.min.json files into CSV flat files, one for each netwrk file
5. Launch Stata and open each flat csv files with it, then save it in Stata format.
6. Use the provided Stata .do scripts to replicate results.

Please note: I use both Stata and Jupyter Notebook interactively, running a block with a few lines of code at a time. Expect to have to change directories, file names etc.

The Online Community Management Software market has witnessed remarkable expansion in recent years, driven by the increasing need for businesses to foster connections among their audiences in an increasingly digital landscape. This software enables organizations to create, manage, and nurture online communities, all

The Online Community Building Platform market has emerged as a pivotal segment in the digital landscape, catering to businesses and organizations seeking to foster engagement and interaction among users. These platforms enable brands to create vibrant online communities where members can connect, share ideas, and co

During an early 2023 survey among marketing professionals worldwide, more than ********* (or ** percent) of respondents reported actively participating in an online community worldwide in the past three months.

The Online Community Engagement Platforms and Software market has seen significant growth and transformation in recent years, emerging as a vital resource for businesses, organizations, and institutions looking to enhance customer interaction and build lasting relationships. These platforms provide comprehensive sol

The Online Community Management Platforms market has emerged as a critical component for organizations looking to foster engagement and build lasting relationships with their audiences in today's digital landscape. These platforms serve as virtual spaces where businesses, brands, and individuals can connect, communi

Malaysia Internet Usage: Social Media/Online Community data was reported at 89.300 % in 2016. This records an increase from the previous number of 80.000 % for 2015. Malaysia Internet Usage: Social Media/Online Community data is updated yearly, averaging 87.100 % from Dec 2014 (Median) to 2016, with 3 observations. The data reached an all-time high of 89.300 % in 2016 and a record low of 80.000 % in 2015. Malaysia Internet Usage: Social Media/Online Community data remains active status in CEIC and is reported by Malaysian Communications and Multimedia Commission. The data is categorized under Global Database’s Malaysia – Table MY.TB003: Telecommunication Statistics: Internet.

The Based SaaS (Software as a Service) Online Community Building Platform market has emerged as a pivotal solution for organizations seeking to foster engagement, collaboration, and knowledge-sharing among their users. This dynamic market, rooted in the increasing demand for connectedness and interaction in various

Context

With roughly 2.89 billion monthly active users as of the second quarter of 2021, Facebook is the biggest social network worldwide. In the third quarter of 2012, the number of active Facebook users surpassed one billion, making it the first social network ever to do so. Active users are those who have logged into Facebook during the past 30 days. During the first quarter of 2021, the company stated that 3.51 billion people were using at least one of the company's core products (Facebook, WhatsApp, Instagram, or Messenger) each month.

Content

This data was collected by Facebook and was released in July 2021.

Explore the booming Social Networking Sites market, projected to reach USD 150,000 million by 2025, driven by entertainment, commerce, and enterprise adoption. Discover key trends, drivers, and regional growth.

Youtube social network and ground-truth communities

https://snap.stanford.edu/data/com-Youtube.html

Dataset information

Youtube (http://www.youtube.com/) is a video-sharing web site that includes a social network. In the Youtube social network, users form friendship each other and users can create groups which other users can join. We consider
such user-defined groups as ground-truth communities. This data is provided by Alan Mislove et al.
(http://socialnetworks.mpi-sws.org/data-imc2007.html)

We regard each connected component in a group as a separate ground-truth
community. We remove the ground-truth communities which have less than 3
nodes. We also provide the top 5,000 communities with highest quality
which are described in our paper (http://arxiv.org/abs/1205.6233). As for
the network, we provide the largest connected component.

Network statistics
Nodes 1,134,890
Edges 2,987,624
Nodes in largest WCC 1134890 (1.000)
Edges in largest WCC 2987624 (1.000)
Nodes in largest SCC 1134890 (1.000)
Edges in largest SCC 2987624 (1.000)
Average clustering coefficient 0.0808
Number of triangles 3056386
Fraction of closed triangles 0.002081
Diameter (longest shortest path) 20
90-percentile effective diameter 6.5
Community statistics
Number of communities 8,385
Average community size 13.50
Average membership size 0.10

Source (citation)
J. Yang and J. Leskovec. Defining and Evaluating Network Communities based on Ground-truth. ICDM, 2012. http://arxiv.org/abs/1205.6233

Files
File Description
com-youtube.ungraph.txt.gz Undirected Youtube network
com-youtube.all.cmty.txt.gz Youtube communities
com-youtube.top5000.cmty.txt.gz Youtube communities (Top 5,000)

Notes on inclusion into the SuiteSparse Matrix Collection, July 2018:

The graph in the SNAP data set is 1-based, with nodes numbered 1 to
1,157,827.

In the SuiteSparse Matrix Collection, Problem.A is the undirected Youtube
network, a matrix of size n-by-n with n=1,134,890, which is the number of
unique user id's appearing in any edge.

Problem.aux.nodeid is a list of the node id's that appear in the SNAP data set. A(i,j)=1 if person nodeid(i) is friends with person nodeid(j). The
node id's are the same as the SNAP data set (1-based).

C = Problem.aux.Communities_all is a sparse matrix of size n by 16,386
which represents the communities in the com-youtube.all.cmty.txt file.
The kth line in that file defines the kth community, and is the column
C(:,k), where C(i,k)=1 if person ...

Context

Riga Data Science Club is a non-profit organisation to share ideas, experience and build machine learning projects together. Data Science community should known own data, so this is a dataset about ourselves: our website analytics, social media activity, slack statistics and even meetup transcriptions!

Content

Dataset is split up in several folders by the context: * linkedin - company page visitor, follower and post stats * slack - messaging and member activity * typeform - new member responses * website - website visitors by country, language, device, operating system, screen resolution * youtube - meetup transcriptions

Inspiration

Let's make Riga Data Science Club better! We expect this data to bring lots of insights on how to improve.

"Know your c̶u̶s̶t̶o̶m̶e̶r̶ member" - Explore member interests by analysing sign-up survey (typeform) responses - Explore messaging patterns in Slack to understand how members are retained and when they are lost

Social media intelligence * Define LinkedIn posting strategy based on historical engagement data * Define target user profile based on LinkedIn page attendance data

Website * Define website localisation strategy based on data about visitor countries and languages * Define website responsive design strategy based on data about visitor devices, operating systems and screen resolutions

Have some fun * NLP analysis of meetup transcriptions: word frequencies, question answering, something else?

Image

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1842206%2Ff84a67b64934ccfdd6fd4bfc24db094d%2F_982f849a-87df-44ff-94ff-3fc97c6198aa-small2.jpeg?generation=1738169001850229&alt=media" alt="">

History

• 03Mar2025- when determining last content shared, I am now using the latest version of Model, Dataset, and Notebook, rather than the creation date of the very first version. I also added the reaction counts which was a new csv added in the MetaKaggle dataset. The discussion can be found here . I also added versions created for Model, Notebook, and Dataset to properly track users that are updating their datasets.
• 04Feb2025- Fixed the issue on ModelUpvotesGiven and ModelUpvotesReceived values being identical

Context

User aggregated stats and data using the Official Meta Kaggle dataset

Note

Expect some discrepancies between the counts seen in your profile, because, aside from there is a lag of one to two days before a new dataset is published, some information such as Kaggle staffs' upvotes and private competitions are not included. But for almost all members, the figures should reconcile

Notebook updater

📊 (Scheduled) Meta Kaggle Users' Stats

Image

Generated with Bing image generator

Summary statistics of the datasets that were used.

Introduction

Social Media Statistics: Over the last twenty years, social media has evolved from specialized online communities into a worldwide network comprising over 5.3 billion users. The growth of social media has been remarkable in recent times. Our methods of interaction have undergone a significant transformation following the emergence of social media. As an inescapable force, social media must occupy a central role in your marketing strategy.

Platforms such as Instagram, Facebook, YouTube, and WhatsApp are instrumental in the distribution of news and information. Given the extensive audience available, it is unthinkable for a business in 2025 to disregard the influence of social media. Social media can improve your engagement with your audience while expanding your market reach and inspiring brand awareness.