Census of Twitter users: Scraping and describing the national network of South Korea

Guan, Lu; Liu, Xiao Fan; Sun, Wu-Jiu; Liang, Hai; Zhu, Jiaming

doi:10.1371/journal.pone.0277549

Cited by 3 publications

(2 citation statements)

References 48 publications

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“…These accounts are displayed on the user's timeline, enabling them to view the tweets and updates from these accounts. The number of friends a user possesses is synonymous with the out-degree of the corresponding node in the graph which yield signi cant insights into the structure and dynamics of social networks (Guan et al, 2022).…”

Section: Number Of Friendsmentioning

confidence: 99%

Generating Attribute Similarity Graphs: A User Behavior-Based Approach from Real- Time Microblogging Data on Platform X

Hasan,

Bakar,

Yaakub

2024

Preprint

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Social network analysis is a powerful tool for understanding various phenomena, but it requires data with explicit connections among users. However, such data is hard to obtain in real-time, especially from platforms like X, commonly known as Twitter, where users share topic-related content rather than personal connections. Therefore, this paper tackles a new problem of building a social network graph in real-time where explicit connections are unavailable. Our methodology is centred around the concept of user similarity as the fundamental basis for establishing connections, suggesting that users with similar characteristics are more likely to form connections. To implement this concept, we extracted easily accessible attributes from the Twitter platform and proposed a novel graph model based on similarity. We also introduce an Attribute-Weighted Euclidean Distance (AWED) to calculate user similarities. We compare the proposed graph with synthetic graphs based on network properties, online social network characteristics, and predictive analysis. The results suggest that the AWED graph provides a more precise representation of the dynamic connections that exist in real-world online social networks, surpassing the inherent constraints of synthetic graphs. We demonstrate that the proposed method of graph construction is simple, flexible, and effective for network analysis tasks.

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Section: Number Of Friendsmentioning

confidence: 99%

Generating Attribute Similarity Graphs: A User Behavior-Based Approach from Real- Time Microblogging Data on Platform X

Hasan,

Bakar,

Yaakub

2024

Preprint

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“…Publicly available databases are often scraped for usage in research, and Hafiz-Henry [7] is an example of this, where they scrape the publicly available IACR-ePrint archive. There are other works [50]- [53] that scrape publicly available Tweets in order to use them for their research. Besides, Twitter/X provides a Python library (https://www.tweepy.org/) to do similar tasks, which suggests that they are ethically not opposed to the usage of publicly shared tweets.…”

Section: B Twittermentioning

confidence: 99%

Private Aggregate Queries to Untrusted Databases

Hafiz,

Gupta,

Wnuck

et al. 2024

Proceedings 2024 Network and Distributed System Security Symposium

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An essential part of ensuring privacy for internet service users is to protect what data they access so that the database host cannot infer sensitive information (e.g., political affiliation, sexual orientation, etc.) from the query pattern to exploit it or share it with third parties. Often, database users submit aggregate queries (e.g., SUM, MEAN, etc.) with searching and filtering constraints to extract statistically meaningful information from a database by seeking the privacy of its query's sensitive values and database interactions. Private information retrieval (PIR), a privacy-preserving cryptographic tool, solves a simplified version of this problem by hiding the database item that a client accesses. Most PIR protocols require the client to know the exact row index of the intended database item, which cannot support the complicated aggregation-based statistical query in a similar setting. Some works in the PIR space contain keyword searching and SQL-like queries, but most need multiple interactions between the PIR client and PIR servers. Some schemes support searching SQL-like expressive queries in a single round but fail to enable aggregate queries. These schemes are the main focus of this paper. To bridge the gap, we have built a general-purpose novel information-theoretic PIR (IT-PIR) framework that permits a user to fetch the aggregated result, hiding all sensitive sections of the complex query from the hosting PIR server in a single round of interaction. In other words, the server will not know which records contribute to the aggregation. We then evaluate the feasibility of our protocol for both benchmarking and real-world application settings. For instance, in a complex aggregate query to the Twitter microblogging database of 1 million tweets, our protocol takes 0.014 seconds for a PIR server to generate the result when the user is interested in one of ∼ 3𝑘 user handles. In contrast, for a much-simplified task, not an aggregate but a positional query, Goldberg's regular IT-PIR (Oakland 2007) takes 1.13 seconds. For all possible user handles, 300𝑘, it takes equal time compared to the regular IT-PIR. This example shows that complicated aggregate queries through our framework do not incur additional overhead if not less, compared to the conventional query.

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Concept and challenges of a social media observatory as a DIY research infrastructure

Wiedemann,

Münch,

Rau

et al. 2023

Publizistik

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This article describes the basic concept, ethical and legal considerations, technical implementation as well as resulting tools and data collections of the Social Media Observatory (SMO). Since 2020, the SMO is developed as an open science research infrastructure within the Research Institute Social Cohesion (RISC) in Germany. It focuses on (the support of) long-term monitoring of public communication on selected platforms and online news media to answer social science-related research questions. Based on systematically compiled lists of public speaker categories, such as parliamentarians or media organizations, it collects statistics as well as content data to study the German social media discourse in comparison to mass media. Aggregated results are published via interactive dashboards. Raw data is published as ID lists for reproduction or shared with researchers upon request. Following a do-it-yourself approach to infrastructure, the SMO further provides various tools, curated datasets, and documented workflows, for instance, to run thematic ad-hoc data collections. As a main feature, it maintains a curated knowledge base in wiki format to enable other researchers to perform systematic social media observations on their own.

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Census of Twitter users: Scraping and describing the national network of South Korea

Cited by 3 publications

References 48 publications

Generating Attribute Similarity Graphs: A User Behavior-Based Approach from Real- Time Microblogging Data on Platform X

Generating Attribute Similarity Graphs: A User Behavior-Based Approach from Real- Time Microblogging Data on Platform X

Private Aggregate Queries to Untrusted Databases

Concept and challenges of a social media observatory as a DIY research infrastructure

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