Questions tagged [social-network-analysis]
Social network data consists of a collection of "nodes" (which can be any sort of entity - e.g. people, corporations) and "links" (which can be any sort of relationship - e.g. friend, sharing a board member).
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What does near-cut (threshold) graph say about original complete weighted graph?
CROSSPOST: https://math.stackexchange.com/q/4588249/117548
ORIGINAL post, preamble
Start from a complete graph with weighted edges (e.g. in $[0,1]$ interval). Continuously increasing threshold $t$ ...
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What are good Bipartite Graphs Algorithms?
Currently, I have a dataset with pairs .
The idea is to detect any anomaly in these relationships. I was able to just use pandas to do the analysis so far.
|Customer|Agent|Duration|Marks|etc
|C1.......
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What explains T5's recent resurgence?
I read on https://towardsdatascience.com/choosing-the-right-language-model-for-your-nlp-use-case-1288ef3c4929:
I find the curve for T5 to be particularly interesting. What explains its recent ...
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Method or tool to simulate weighted graphs with a specified weighted degree sequence
Are you aware of a method or tool to simulate a graph with that has a specified weighted degree sequence? They would be used to generate a distribution of bootstrap replicates.
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Calculating similarity score between nodes with the significance of their indexes
I have two excel files :
In the first file, each row represent node number and its features as
232 1 0 0 1 0 1
477 1 1 0 0 0 0
In the second file, each ...
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Network Visualisation (Python/Excel)
I have a large data set similar to that in the screenshot below:
and I want to visualise the whole data set like the diagram below (made with a lot of effort in PowerPoint!)
Is there any way to do ...
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May high closeness centrality in email graph be interpreted as high involvement?
I have a network graph where nodes are email addresses and their connections are emails they send to each other. I have calculated closeness centrality for each node and got couple with very high ...
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Twitter data scraping: API vs Advabced Search
Need to analyze tweets on a specific topic, my application (for using Twitter API) was not approved. Instead, I tried to do it manually using Twitter Advanced Search. However it's more burdensome than ...
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Multi-attribute pandas data frame to a weighted network - how to manage attribute values as weights?
I have a pandas data frame that includes n rows, indicating people, with m columns, indicating a number of attributes that they've been rated on (fictitious working example here).
The data frame looks ...
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Social Media Analysis (Brandwatch, TalkWalker etc.)
I'm trying to build a simplified version of existing software that do social media analysis, such as Brandwatch.
I've seen Mining the Social Web by Matthew Russell ...
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How do work around Kmeans value error?
I am working on a social network analysis project. My data comes from twitter. Before I run the analysis, I intend to apply clustering- specifically Kmeans to determine how to seperate tweets in ...
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Is there a metric for "cliquiness" for social graphs?
Regarding social network graphs, let us say that I am connected to 10 people, and that each of them are connected to 10 people. At one extreme this means that I have 100 unique $2^{nd}$ degree ...
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Constructing a Weighted Random Graph [closed]
I want to create a weighted random graph (in contrast to the unweighted Erdős–Rényi model). I have a list of weights (derived from a real-world network, very skewed distribution that most weights are ...
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Reduce size of a network graph for bipartite projection
I have a graph that I created from a pandas data frame. The length of the graph is ~450k edges. When I try to run the weighted_projected_graph function, it runs for ...
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Extract data from facebook
I am learning about social media analysis. I am aware that we can extract the data from twitter using hashtags and API. Ex; If I use #covid19, I will get all tweets ...
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Biasing SVM algorithm towards particular subset of data
I'm training an SVM model for sentiment analysis, based on social media data eg. tweets.
The model will be trained using a small selection of a particular company's tweets in order to classify new ...
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Data mining: Clique based clustering to make comparison in social network analysis
I am a very beginner in data mining. I want to work on Clique based clustering method. I want to make a comparison between various datasets for social network analysis or community detection of social ...
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How to create new graph vertices from existing one with igraph in R?
I have the following DF in R representing a directed graph:
...
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Spread of infection: how to correct for population size
The Covid-19 death data for different countries should reflect how fast the infection spreads through the population and how susceptible the population is.
The total number of deaths after some longer ...
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Scalable way to calculate betweenness centrality for a graph in spark
I have a use-case to calculate betweenness centrality of nodes. I have tried graphx with spark-betweenness but it is a very long running job. Has anyone successfully calculated betweenness centrality ...
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Need some advice on approach to select only the informative emojis from the data set?
I have a giant data set from a local elections, which contains hashtags, emojis, and comments. I wanted to make a network analysis using only emojis.
So far I have a network analysis graph made in R ...
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Counting Number of Parameters in Neural Networks [closed]
Note: This is an academics based problem.
So in a recent in-class quiz, we were asked that if we have an input layer consisting of 20 nodes along with 2 hidden layers (one of size 10 and the other of ...
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NLP: Getting the top 5 or top 10 predictions
I am working on a social networking application and I have to make its news feed better. For example: If someone searches for 'suggest me some good books', it should yield some names.
Now, I have ...
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Label Propagation for weighted graph
I am working on "community detection" on a big network graph and I've been using the Label Propagation Algorithm from GraphFrames (Spark package).
However, my graph is weighted and I was wondering ...
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measuring flip-flop behaviour across several topics
I'm trying to analyze a behavior called "sentiment flipping" of users in a dataset, but I'm not able to step on.
Let's suppose that I have two groups of users, say them good and bad users.
My ...
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Correlation between (average daily) impressions and user response ratio in social media
I'm doing a preliminary study on data from a (niche) social media platform. Studying the correlations between impressions of an object (aka views), interactions (aka likes, comments, ...) and their ...
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Twitter Dataset
I have found the following dataset, apparently it is the largest tweet dataset:
https://www.kaggle.com/kazanova/sentiment140
However, I am looking for a dataset of tweets, with columns containing:
...
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Retrieving follower and followee (friend) counts using Twitter API
I want to retrieve Twitter users' follower and followee (friend) count using Twitter API. (I am reluctant with using a crawler ...
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Name of this type of cross variable interaction Plot
In recent papers of Social Network Analysis , I have been observing this particular type of graph used increasingly. I looked for what they are called to replicate the graph, but couldn't find the ...
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Are social network analysis and graph analytics the same thing?
Are social network analysis and graph analytics the same thing? If not, what are the differences? Is social network analysis perhaps a subset of graph analytics?
Are they just modern extensions of ...
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Protein interaction prediction- how to input this data structure
I know the basics of machine learning and have quite an experience with time series data or data fed in a tabular format. But in the picture, the data is arranged as a graph. Is there a way to input ...
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How to retrieve Twitter username with UUID
I am trying to analyze FakeNewsNet which is a fake news dataset for Social Network Analysis.
There are UUID(I am not sure about the entity name)s of users in the ...
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Does anyone have examples of using graph theory/network science in the field of Business Intelligence? [closed]
A lot of examples for the use of graph theory revolve around either social networks (which I understand are useful for business intelligence) or scientific/biological application.
I am exploring the ...
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How to do hidden variable learning in Bayesian Network with Python?
I learned how to use libpgm in general for Bayesian inference and learning, but I do not understand if I can use it for learning with hidden variable.
More precisely, I am trying to implement approach ...
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Twitter Retweet Network Visualization
I am trying to visualize retweet network in order to find out which users are most likely to have most influence on other users. Here is my code:
...
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Are they any technical SNA tutorials that focus on real-world business problems?
Most of the technical (e.g. NetworkX, iGraph, Gephi) SNA tutorials I see focus on "toy" examples. They show how to run various algorithms, but it's not clear what real problems these would solve---...
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Link Prediction based Similarity Indices
So, I was reading some Link Prediction based algorithms and similarity indices. I came across two random walk based indices - Local Random Walk(LRW) and Superposed Random Walk(SRW). I read the ...
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Representing a community as a vector
My setup is this:
Suppose I have transactional data over a large period of time. The parties of each transaction are labled, and I use Louvain algorithm for detecting communities (and sub-communities)...
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Seminal papers about analysis and application based on publicly released data [closed]
The US government releases a lot of varied data here. Data science and data analytics have greatly matured over the last decade varying from Cambridge Analytica on one extreme to Google/Amazon Ads ...
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Is there a way to combine both ties (nondirected edges) and wins/losses (directed edges) in a single social network?
I'm currently building social networks for small colonies of animals which I've observed, with the aim of comparing changes in social network structure in response to changes in certain environmental ...
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Voting patterns similarities
I'm interested in any research materials on voting patterns.
I have a data set of how PMs (members of parliament) voted in my country during last couple of years. Each PM has 3 buttons: Yes, No, ...
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Can we access social media advertisements and information like how many likes, comments, shares they received using their APIs?
I want to access social media advertisements and information about how popular they were ( how many likes, comments and shares they received and the comments). Can I get these information using these ...
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Extract details from bibliometrics data
I have set of bibliometrics data (references). I want to extract the author names, title and the name of the conference/journal from it. Since the referencing style used by different papers vary, I am ...
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Echo-Effect-Metric Network
I have been working on data science project where I am trying to build a metric for how inbred a source is in a network. We hope to apply this to intelligence reporting, in which documents tend to ...
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Building a Citation Network to Analyze in R
I am working on network analysis project at one of our Nation's Service Academies, and I need a little help.
As a starting point, we are looking at a citation network that we build by using the ...
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Identify social users using graph embeddings
I have a social network and I want to identify the most social people in the graph. In a typical graph experiments this could have done using different network features.
However, I recently came ...
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On Creating an Interoperable Network Matrix
Complete self taught novice here.
Question
Are there any popular standards, or commonly used formats for representing/saving/sharing/serializing a network?
Background
I built a simple but very large (...
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Why an eigenvector might be reasonable notion of centrality
Using adjacency matrix to represent a connection between node i and node j, 1 means connected and 0 means not connected.
Using eigenvector to represent the centrality means the more nodes with high ...
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Visualizing community composition using network of pie charts
Given a social network, I want to perform community detection and compare the result to known node metadata, such as gender, age, etc. to see if certain communities are largely composed of "similar" ...
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Can we apply community detection algorithms for word vector space?
As I understand we can apply community detection algorithms such as Louvain to detect communities in a social network (i.e. involves people).
But I am quite interested in knowing if we can use the ...
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