In the third quarter of 2023, Facebook was the leading social media in France with more than 72.3 percent of French online users accessing the social media platform on a monthly basis. The most popular messaging platform was WhatsApp, with 63.7 percent of surveyed French internet users reporting to have used the platform. Additionally, Instagram was used by 60.3 percent of respondents.

Youtube social network and ground-truth communities Dataset information Youtube 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.

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. As for the network, we provide the largest connected component.

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

Survey findings showed that Facebook was the most frequently used social network for news access in France in 2024, with more than ** percent of respondents using the platform for news every week. YouTube and WhatsApp rounded out the top three that year. Social media usage is soaring in France The number of social media users in France has steadily increased since the start of the new millennium. Today, an estimated ** million people have an account on one of the various social networks to post pictures and videos, communicate with friends and strangers, stay up to date with their favorite celebrities and influencers, or catch up on news headlines. While video-sharing apps such as TikTok have shaken up the scene and amassed millions of users recently, Facebook remains the most popular social media platform in France, followed by Messenger, WhatsApp, and Instagram – all Meta-owned properties. Audiences lack trust in social media news Even though millions of social media users check their feeds for news each day, recent reports have indicated that a significant share of French online users are wary of news reports circulating on platforms such as Facebook. Less than ** percent of survey respondents felt confident about the accuracy of posts shared on social media by official channels in 2021. Meanwhile, French adults' trust in news on social media was even lower for information shared online by friends. Many French social media users stated they regularly encountered false news on their feeds, explaining why social media stands out as the least trustworthy news source according to French consumers.

In 2023, the most used type of online network in France was instant messengers such as WhatsApp, Facebook Messenger, and WeChat, with 66 percent of users saying they used this kind of platform regularly. Overall, 64 percent of users in France reported using social networking platforms regularly, such as Facebook. Only eight percent of users used discussion forums, such as Reddit and Quora, on a regular basis.

ABSTRACT

The Albero study analyzes the personal transitions of a cohort of high school students at the end of their studies. The data consist of (a) the longitudinal social network of the students, before (n = 69) and after (n = 57) finishing their studies; and (b) the longitudinal study of the personal networks of each of the participants in the research. The two observations of the complete social network are presented in two matrices in Excel format. For each respondent, two square matrices of 45 alters of their personal networks are provided, also in Excel format. For each respondent, both psychological sense of community and frequency of commuting is provided in a SAV file (SPSS). The database allows the combined analysis of social networks and personal networks of the same set of individuals.

INTRODUCTION

Ecological transitions are key moments in the life of an individual that occur as a result of a change of role or context. This is the case, for example, of the completion of high school studies, when young people start their university studies or try to enter the labor market. These transitions are turning points that carry a risk or an opportunity (Seidman & French, 2004). That is why they have received special attention in research and psychological practice, both from a developmental point of view and in the situational analysis of stress or in the implementation of preventive strategies.

The data we present in this article describe the ecological transition of a group of young people from Alcala de Guadaira, a town located about 16 kilometers from Seville. Specifically, in the “Albero” study we monitored the transition of a cohort of secondary school students at the end of the last pre-university academic year. It is a turning point in which most of them began a metropolitan lifestyle, with more displacements to the capital and a slight decrease in identification with the place of residence (Maya-Jariego, Holgado & Lubbers, 2018).

Normative transitions, such as the completion of studies, affect a group of individuals simultaneously, so they can be analyzed both individually and collectively. From an individual point of view, each student stops attending the institute, which is replaced by new interaction contexts. Consequently, the structure and composition of their personal networks are transformed. From a collective point of view, the network of friendships of the cohort of high school students enters into a gradual process of disintegration and fragmentation into subgroups (Maya-Jariego, Lubbers & Molina, 2019).

These two levels, individual and collective, were evaluated in the “Albero” study. One of the peculiarities of this database is that we combine the analysis of a complete social network with a survey of personal networks in the same set of individuals, with a longitudinal design before and after finishing high school. This allows combining the study of the multiple contexts in which each individual participates, assessed through the analysis of a sample of personal networks (Maya-Jariego, 2018), with the in-depth analysis of a specific context (the relationships between a promotion of students in the institute), through the analysis of the complete network of interactions. This potentially allows us to examine the covariation of the social network with the individual differences in the structure of personal networks.

PARTICIPANTS

The social network and personal networks of the students of the last two years of high school of an institute of Alcala de Guadaira (Seville) were analyzed. The longitudinal follow-up covered approximately a year and a half. The first wave was composed of 31 men (44.9%) and 38 women (55.1%) who live in Alcala de Guadaira, and who mostly expect to live in Alcala (36.2%) or in Seville (37.7%) in the future. In the second wave, information was obtained from 27 men (47.4%) and 30 women (52.6%).

DATE STRUCTURE AND ARCHIVES FORMAT

The data is organized in two longitudinal observations, with information on the complete social network of the cohort of students of the last year, the personal networks of each individual and complementary information on the sense of community and frequency of metropolitan movements, among other variables.

Social network

The file “Red_Social_t1.xlsx” is a valued matrix of 69 actors that gathers the relations of knowledge and friendship between the cohort of students of the last year of high school in the first observation. The file “Red_Social_t2.xlsx” is a valued matrix of 57 actors obtained 17 months after the first observation.

The data is organized in two longitudinal observations, with information on the complete social network of the cohort of students of the last year, the personal networks of each individual and complementary information on the sense of community and frequency of metropolitan movements, among other variables.

In order to generate each complete social network, the list of 77 students enrolled in the last year of high school was passed to the respondents, asking that in each case they indicate the type of relationship, according to the following values: 1, “his/her name sounds familiar"; 2, "I know him/her"; 3, "we talk from time to time"; 4, "we have good relationship"; and 5, "we are friends." The two resulting complete networks are represented in Figure 2. In the second observation, it is a comparatively less dense network, reflecting the gradual disintegration process that the student group has initiated.

Personal networks

Also in this case the information is organized in two observations. The compressed file “Redes_Personales_t1.csv” includes 69 folders, corresponding to personal networks. Each folder includes a valued matrix of 45 alters in CSV format. Likewise, in each case a graphic representation of the network obtained with Visone (Brandes and Wagner, 2004) is included. Relationship values range from 0 (do not know each other) to 2 (know each other very well).

Second, the compressed file “Redes_Personales_t2.csv” includes 57 folders, with the information equivalent to each respondent referred to the second observation, that is, 17 months after the first interview. The structure of the data is the same as in the first observation.

Sense of community and metropolitan displacements

The SPSS file “Albero.sav” collects the survey data, together with some information-summary of the network data related to each respondent. The 69 rows correspond to the 69 individuals interviewed, and the 118 columns to the variables related to each of them in T1 and T2, according to the following list:

 • Socio-economic data.


 • Data on habitual residence.


 • Information on intercity journeys.


 • Identity and sense of community.


 • Personal network indicators.


 • Social network indicators.

DATA ACCESS

Social networks and personal networks are available in CSV format. This allows its use directly with UCINET, Visone, Pajek or Gephi, among others, and they can be exported as Excel or text format files, to be used with other programs.

The visual representation of the personal networks of the respondents in both waves is available in the following album of the Graphic Gallery of Personal Networks on Flickr: .

In previous work we analyzed the effects of personal networks on the longitudinal evolution of the socio-centric network. It also includes additional details about the instruments applied. In case of using the data, please quote the following reference:

Maya-Jariego, I., Holgado, D. & Lubbers, M. J. (2018). Efectos de la estructura de las redes personales en la red sociocéntrica de una cohorte de estudiantes en transición de la enseñanza secundaria a la universidad. Universitas Psychologica, 17(1), 86-98. https://doi.org/10.11144/Javeriana.upsy17-1.eerp

The English version of this article can be downloaded from: https://tinyurl.com/yy9s2byl

CONCLUSION

The database of the “Albero” study allows us to explore the co-evolution of social networks and personal networks. In this way, we can examine the mutual dependence of individual trajectories and the structure of the relationships of the cohort of students as a whole. The complete social network corresponds to the same context of interaction: the secondary school. However, personal networks collect information from the different contexts in which the individual participates. The structural properties of personal networks may partly explain individual differences in the position of each student in the entire social network. In turn, the properties of the entire social network partly determine the structure of opportunities in which individual trajectories are displayed.

The longitudinal character and the combination of the personal networks of individuals with a common complete social network, make this database have unique characteristics. It may be of interest both for multi-level analysis and for the study of individual differences.

ACKNOWLEDGEMENTS

The fieldwork for this study was supported by the Complementary Actions of the Ministry of Education and Science (SEJ2005-25683), and was part of the project “Dynamics of actors and networks across levels: individuals, groups, organizations and social settings” (2006 -2009) of the European Science Foundation (ESF). The data was presented for the first time on June 30, 2009, at the European Research Collaborative Project Meeting on Dynamic Analysis of Networks and Behaviors, held at the Nuffield College of the University of Oxford.

REFERENCES

Brandes, U., & Wagner, D. (2004). Visone - Analysis and Visualization of Social Networks. In M. Jünger, & P. Mutzel (Eds.), Graph Drawing Software (pp. 321-340). New York: Springer-Verlag.

Maya-Jariego, I. (2018). Why name generators with a fixed number of alters may be a pragmatic option for personal network analysis. American Journal of

To identify relevant actors for the governance of co-produced forest nature's contributions to people (NCP) the researchers conducted a social-network analysis based on 39 semi-structured interviews with foresters and conservation managers. These interviews were conducted across three case study sites in Germany: Schorfheide-Chorin in the Northeast, Hainich-Dün in the Centre, and Schwäbische Alb in the Southwest. All three case study sites belong to the large-scale and long-term research platform Biodiversity Exploratories. The researchers employed a predefined coding set to analyse the interviews and grasp the relationships between different actors based on the anthropogenic capitals they used to co-produce forest nature's contributions to people (NCP). To secure the interviewees anonymity this coding cannot be published. Therefore, this data set is limited to this coding set.

According to a 2022 survey conducted in France, social network usage penetration varies across different age groups. Almost seven out of every 10 respondents aged 12 to 17 reported using social networks. The usage rate was higher among the 18 to 24 years age group, with 79 percent of respondents indicating social network usage. In contrast, social network usage among French individuals aged 70 years and older was comparatively lower at 27 percent.

Dataset Card for Social Network Ads Dataset

  Dataset Summary

The Social Network Ads Dataset is an English Language dataset containing 400 entries of customer information and their purchasing behavior

  Dataset Structure





  Data Instances

For each instance, there is an integer for the age, an integer for the estimated salary, and the purchased feature has 2 possible values , 0 and 1 which correspond to No and Yes respectively. {'Age': '19'… See the full description on the dataset page: https://huggingface.co/datasets/saifhmb/social-network-ads.

We asked French consumers about "Social network usage by brand" and found that "Facebook" takes the top spot, while "Yelp" is at the other end of the ranking.These results are based on a representative online survey conducted in 2024 among ****** consumers in France.

This fileset contains data related to our paper "Towards reproducibility in online social network research". This paper firstly comprises a survey of OSN papers, and the bibliographic details for these papers are contained here in a JSON file. The paper also attempts to reproduce an existing OSN paper using our PRISONER system, and the policy for this is contained here in an XML file.

This statistic shows the share of individuals in France who participated in social networks from 2011 to 2019. In 2019, 42 percent of all individuals used social networks in France.

This chart shows social media use among enterprises by industry in France in 2019. On average in 2019, 49 percent of French enterprises were present on social networking sites. In the information, communication and computer repair industry, 82 percent of surveyed enterprises used social media.

Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other attribute information can be effectively preserved. Network representation leaning facilitates further applications such as classification, link prediction, anomaly detection, and clustering. In addition, techniques based on deep neural networks have attracted great interests over the past a few years. In this survey, we conduct a comprehensive review of the current literature in network representation learning, utilizing neural network models. First, we introduce the basic models for learning node representations in homogeneous networks. We will also introduce some extensions of the base models, tackling more complex scenarios such as analyzing attributed networks, heterogeneous networks, and dynamic networks. We then introduce techniques for embedding subgraphs and also present the applications of network representation learning. Finally, we discuss some promising research directions for future work.

Financial overview and grant giving statistics of International Network for Social Network Analysis Association

Social network analysis is an important problem in data mining. A fundamental step for analyzing social networks is to encode network data into low-dimensional representations, i.e., network embeddings, so that the network topology structure and other attribute information can be effectively preserved. Network representation leaning facilitates further applications such as classification, link prediction, anomaly detection, and clustering. In addition, techniques based on deep neural networks have attracted great interests over the past a few years. In this survey, we conduct a comprehensive review of the current literature in network representation learning, utilizing neural network models. First, we introduce the basic models for learning node representations in homogeneous networks. We will also introduce some extensions of the base models, tackling more complex scenarios such as analyzing attributed networks, heterogeneous networks, and dynamic networks. We then introduce techniques for embedding subgraphs and also present the applications of network representation learning. Finally, we discuss some promising research directions for future work.

This dataset is structured as a graph, where nodes represent users and edges capture their interactions, including tweets, retweets, replies, and mentions. Each node provides detailed user attributes, such as unique ID, follower and following counts, and verification status, offering insights into each user's identity, role, and influence in the mental health discourse. The edges illustrate user interactions, highlighting engagement patterns and types of content that drive responses, such as tweet impressions. This interconnected structure enables sentiment analysis and public reaction studies, allowing researchers to explore engagement trends and identify the mental health topics that resonate most with users.

The dataset consists of three files: 1. Edges Data: Contains graph data essential for social network analysis, including fields for UserID (Source), UserID (Destination), Post/Tweet ID, and Date of Relationship. This file enables analysis of user connections without including tweet content, maintaining compliance with Twitter/X’s data-sharing policies. 2. Nodes Data: Offers user-specific details relevant to network analysis, including UserID, Account Creation Date, Follower and Following counts, Verified Status, and Date Joined Twitter. This file allows researchers to examine user behavior (e.g., identifying influential users or spam-like accounts) without direct reference to tweet content. 3. Twitter/X Content Data: This file contains only the raw tweet text as a single-column dataset, without associated user identifiers or metadata. By isolating the text, we ensure alignment with anonymization standards observed in similar published datasets, safeguarding user privacy in compliance with Twitter/X's data guidelines. This content is crucial for addressing the research focus on mental health discourse in social media. (References to prior Data in Brief publications involving Twitter/X data informed the dataset's structure.)

Forecast: Individuals Participating in Online Social Networks in France 2024 - 2028 Discover more data with ReportLinker!

A dataset of mentions, growth rate, and total volume of the keyphrase 'Social Network' over time.

Forecast: Individuals Participating in Online Social Networks in île De France (France) 2024 - 2028 Discover more data with ReportLinker!

France - Individuals using the internet for participating in social networks was 44.39% in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for France - Individuals using the internet for participating in social networks - last updated from the EUROSTAT on July of 2025. Historically, France - Individuals using the internet for participating in social networks reached a record high of 44.83% in December of 2021 and a record low of 35.55% in December of 2011.