How much time do people spend on social media? As of 2019 and 2020, the average daily social media usage of internet users worldwide amounted to *** minutes per day, up from *** minutes in the previous year. Currently, the country with the most time spent on social media per day is the Philippines, with online users spending an average of ***** hours and ** minute on social media each day. In comparison, the daily time spent with social media in the U.S. was just *** hours and ***** minutes. Global social media usageCurrently, the global social network penetration rate is nearly ** percent. Western Europe had a ** percent social media penetration rate, topping the ranking of global social media usage by region. Eastern and Middle Africa closed the ranking with *** and ***** percent usage reach, respectively. People access social media for a variety of reasons. Users like to find funny or entertaining content and enjoy sharing photos and videos with friends, but mainly use social media to stay in touch with current events friends. Global impact of social mediaSocial media has a wide-reaching and significant impact on not only online activities but also offline behavior and life in general. During a global online user survey in February 2019, a significant share of respondents stated that social media had increased their access to information, ease of communication, and freedom of expression. On the flipside, respondents also felt that social media had worsened their personal privacy, increased a polarization in politics and heightened everyday distractions.

General data recollected for the studio " Analysis of the Quantitative Impact of Social Networks on Web Traffic of Cybermedia in the 27 Countries of the European Union". Four research questions are posed: what percentage of the total web traffic generated by cybermedia in the European Union comes from social networks? Is said percentage higher or lower than that provided through direct traffic and through the use of search engines via SEO positioning? Which social networks have a greater impact? And is there any degree of relationship between the specific weight of social networks in the web traffic of a cybermedia and circumstances such as the average duration of the user's visit, the number of page views or the bounce rate understood in its formal aspect of not performing any kind of interaction on the visited page beyond reading its content? To answer these questions, we have first proceeded to a selection of the cybermedia with the highest web traffic of the 27 countries that are currently part of the European Union after the United Kingdom left on December 31, 2020. In each nation we have selected five media using a combination of the global web traffic metrics provided by the tools Alexa (https://www.alexa.com/), which ceased to be operational on May 1, 2022, and SimilarWeb (https:// www.similarweb.com/). We have not used local metrics by country since the results obtained with these first two tools were sufficiently significant and our objective is not to establish a ranking of cybermedia by nation but to examine the relevance of social networks in their web traffic. In all cases, cybermedia whose property corresponds to a journalistic company have been selected, ruling out those belonging to telecommunications portals or service providers; in some cases they correspond to classic information companies (both newspapers and televisions) while in others they refer to digital natives, without this circumstance affecting the nature of the research proposed.
Below we have proceeded to examine the web traffic data of said cybermedia. The period corresponding to the months of October, November and December 2021 and January, February and March 2022 has been selected. We believe that this six-month stretch allows possible one-time variations to be overcome for a month, reinforcing the precision of the data obtained. To secure this data, we have used the SimilarWeb tool, currently the most precise tool that exists when examining the web traffic of a portal, although it is limited to that coming from desktops and laptops, without taking into account those that come from mobile devices, currently impossible to determine with existing measurement tools on the market. It includes:

Web traffic general data: average visit duration, pages per visit and bounce rate Web traffic origin by country Percentage of traffic generated from social media over total web traffic Distribution of web traffic generated from social networks Comparison of web traffic generated from social netwoks with direct and search procedures

As of April 2024, around 16.5 percent of global active Instagram users were men between the ages of 18 and 24 years. More than half of the global Instagram population worldwide was aged 34 years or younger.

              Teens and social media

              As one of the biggest social networks worldwide, Instagram is especially popular with teenagers. As of fall 2020, the photo-sharing app ranked third in terms of preferred social network among teenagers in the United States, second to Snapchat and TikTok. Instagram was one of the most influential advertising channels among female Gen Z users when making purchasing decisions. Teens report feeling more confident, popular, and better about themselves when using social media, and less lonely, depressed and anxious.
              Social media can have negative effects on teens, which is also much more pronounced on those with low emotional well-being. It was found that 35 percent of teenagers with low social-emotional well-being reported to have experienced cyber bullying when using social media, while in comparison only five percent of teenagers with high social-emotional well-being stated the same. As such, social media can have a big impact on already fragile states of mind.

Suicide is not only an individual phenomenon, but it is also influenced by social and environmental factors. With the high suicide rate and the abundance of social media data in South Korea, we have studied the potential of this new medium for predicting completed suicide at the population level. We tested two social media variables (suicide-related and dysphoria-related weblog entries) along with classical social, economic and meteorological variables as predictors of suicide over 3 years (2008 through 2010). Both social media variables were powerfully associated with suicide frequency. The suicide variable displayed high variability and was reactive to celebrity suicide events, while the dysphoria variable showed longer secular trends, with lower variability. We interpret these as reflections of social affect and social mood, respectively. In the final multivariate model, the two social media variables, especially the dysphoria variable, displaced two classical economic predictors – consumer price index and unemployment rate. The prediction model developed with the 2-year training data set (2008 through 2009) was validated in the data for 2010 and was robust in a sensitivity analysis controlling for celebrity suicide effects. These results indicate that social media data may be of value in national suicide forecasting and prevention.

Data linked to the Springer Nature 2017 social media and scholarly collaboration network survey

In 2023, Meta Platforms had a total annual revenue of over 134 billion U.S. dollars, up from 116 billion in 2022. LinkedIn reported its highest annual revenue to date, generating over 15 billion USD, whilst Snapchat reported an annual revenue of 4.6 billion USD.

This is the replication package for "Social Networks with Unobserved Links," accepted in 2022 by the Journal of Political Economy.

These files contain Stata (v11/12) do and dta files necessary to produce the results from the 1992 CNES, 1996 ISL, and 2008-09 ANES presented in the article: Djupe, Paul A., Scott D. McClurg, and Anand E. Sokhey. Forthcoming. “The Political Consequences of Gender in Social Networks.” British Journal of Political Science.

Please navigate to http://dx.doi.org/10.7910/DVN/E46ZNK for the full set of replication files. Those files contain Stata (v11/12) do and dta files necessary to produce the results from the 1992 CNES, 1996 ISL, and 2008-09 ANES presented in the article: Djupe, Paul A., Scott D. McClurg, and Anand E. Sokhey. Forthcoming. “The Political Consequences of Gender in Social Networks.” British Journal of Political Science.

This is a JSON export of the CiteULike group at http://www.citeulike.org/groupfunc/19063/home. This contains all of the papers that were surveyed in our paper "Towards reproducibility in online social network research".

Tags are used to group papers by their venue, and to indicate whether the paper meets each of the ten metrics discussed in the paper. These tags are:

VENUES

asonam - Advances in Social Network Analysis and Mining (ASONAM) cacm - Communications of the ACM ccs - ACM Conference on Computer and Communications Security (CCS) chb - Computers in Human Behavior (CHB) chi - ACM Conference on Human Factors in Computing Systems (CHI) com-comms - Computer Communications computer-networks - Computer Networks cosn - Conference on Online Social Networks (COSN) cscw - ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) eurosys-sns - ACM EuroSys Workshop on Social Network Systems (SNS) hotsocial - ACM International Workshop on Hot Topics on Interdisciplinary Social Networks Research (HotSocial) icwsm - International Conference on Weblogs and Social Media (ICWSM) jcmc - Journal of Computer-Mediated Communication (JCMC) nature-journal - Nature ndss - Network and Distributed System Security Symposium (NDSS) pervasive - International Conference on Pervasive Computing pervasive-journal - IEEE Pervasive Computing pnas - Proceedings of the National Academy of Sciences of the United States of America (PNAS) science-journal - Science sn-journal - Social Networks soups - Symposium On Usable Privacy and Security (SOUPS) sp - IEEE Symposium on Security and Privacy tmc - IEEE Transactions on Mobile Computing (TMC) ubicomp - ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) websci - ACM Web Science Conference (WebSci) wosn - Workshop on Online Social Networks (WOSN) wpes - Workshop on Privacy in the Electronic Society (WPES)

METRICS

Each metric tag is appended with either '-0' to denote the paper did not achieve this metric, or '-1' if it did. metric-brief - Participants were briefed/debriefed metric-consent - Participants' consent was sought metric-irb - Ethics approval procedures discussed metric-length - Length of data collection disclosed metric-n - Number of participants disclosed metric-processing - Data-handling strategy discussed metric-protocol - Code and scripts for recreating experiment/analyses shared metric-sampling - Participant sampling strategy discussed metric-shared - Data was shared metric-sourcesns - The OSN(s) from which data are collected disclosed

MISC

yes - Paper met eligibility criteria and was analysed further no - Paper met search term but was not relevant to survey done - Paper has been analysed

The purpose of the dataset is to enable the replication of results as reported in the article: Bonsaksen, T., Price, D., Lamph, G., Kabelenga, I., & Geirdal, A. Ø. (2025). Sleep problems were unrelated to social media use in the late COVID-19 pandemic phase: A cross-national study. PLOS ONE 20(1): e0318507. https://doi.org/10.1371/journal.pone.0318507. The data on sleep problems, psychosocial stress and social media use is uploaded as an SPSS file. Additional information to facilitate using the data can be found in the ReadMe file. The article aimed to explore the relationship between social media use and sleep problems in a cross-national sample two years after the pandemic began. It involved 1405 adults from four countries who completed an online survey. Statistical analyses included independent samples t-tests, Chi-Squared tests, and logistic regression. Among the 858 participants (61.1%) who reported recent sleep problems, 41.1% (353 individuals) attributed these issues to their COVID-19 experiences. Adjusting for age, gender, employment, and psychological distress showed that more hours of social media use were not significantly linked to sleep problems. However, being older, female, employed, and experiencing higher psychological distress were associated with more sleep issues.

As of April 2024, almost 32 percent of global Instagram audiences were aged between 18 and 24 years, and 30.6 percent of users were aged between 25 and 34 years. Overall, 16 percent of users belonged to the 35 to 44 year age group.

              Instagram users

              With roughly one billion monthly active users, Instagram belongs to the most popular social networks worldwide. The social photo sharing app is especially popular in India and in the United States, which have respectively 362.9 million and 169.7 million Instagram users each.

              Instagram features

              One of the most popular features of Instagram is Stories. Users can post photos and videos to their Stories stream and the content is live for others to view for 24 hours before it disappears. In January 2019, the company reported that there were 500 million daily active Instagram Stories users. Instagram Stories directly competes with Snapchat, another photo sharing app that initially became famous due to it’s “vanishing photos” feature.
              As of the second quarter of 2021, Snapchat had 293 million daily active users.

Data produced in Impact-of-social-media-on-suicide-rates .

Acknowledgements:

WHO data export (https://apps.who.int/gho/athena/api/GHO/SDGSUICIDE.csv) was used bound by the following poilcy: https://www.who.int/about/who-we-are/publishing-policies/data-policy

Kaggle dataset regarding social media usage was used (https://www.kaggle.com/margarethamartinez/socialmedia2021) with additional acknowledgements of the original sources necessary:

Acknowledgements:

Facebook: https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/

Twitter: https://investor.twitterinc.com/home/default.aspx

Instagram: https://investor.fb.com/home/default.aspx

Abstract (en): Social networks can shape many aspects of social and economic activity: migration and trade, job-seeking, innovation, consumer preferences and sentiment, public health, social mobility, and more. In turn, social networks themselves are associated with geographic proximity, historical ties, political boundaries, and other factors. Traditionally, the unavailability of large-scale and representative data on social connectedness between individuals or geographic regions has posed a challenge for empirical research on social networks. More recently, a body of such research has begun to emerge using data on social connectedness from online social networking services such as Facebook, LinkedIn, and Twitter. To date, most of these research projects have been built on anonymized administrative microdata from Facebook, typically by working with coauthor teams that include Facebook employees. However, there is an inherent limit to the number of researchers that will be able to work with social network data through such collaborations. In this paper, we therefore introduce a new measure of social connectedness at the US county level. Our Social Connectedness Index is based on friendship links on Facebook, the global online social networking service. Specifically, the Social Connectedness Index corresponds to the relative frequency of Facebook friendship links between every county-pair in the United States, and between every US county and every foreign country. Given Facebook's scale as well as the relative representativeness of Facebook's user body, these data provide the first comprehensive measure of friendship networks at a national level.

Data includes the metadata and links for images posted to social media with CUI redacted. This dataset is associated with the following publication: Angradi, T., J. Launspach, and R. Debbout. Determining preferences for ecosystem benefits in Great Lakes Areas of Concern from photographs posted to social media. JOURNAL OF GREAT LAKES RESEARCH. International Association for Great Lakes Research, Ann Arbor, MI, USA, 44(2): 340-351, (2018).

Journal of business analytics Impact Factor 2024-2025 - ResearchHelpDesk - Business analytics research focuses on developing new insights and a holistic understanding of an organisation’s business environment to help make timely and accurate decisions, and to survive, innovate and grow. Thus, business analytics draws on the full spectrum of descriptive/diagnostic, predictive and prescriptive analytics in order to make better (i.e., data-driven and evidence-based) decisions to create business value in the broadest sense. The mission of the Journal of Business Analytics Journal (JBA) is to serve the emerging and rapidly growing community of business analytics academics and practitioners. We aim to publish articles that use real-world data and cases to tackle problem situations in a creative and innovative manner. We solicit articles that address an interesting research problem, collect and/or repurpose multiple types of data sets, and develop and evaluate analytics methods and methodologies to help organisations apply business analytics in new and novel ways. Reports of research using qualitative or quantitative approaches are welcomed, as are interdisciplinary and mixed methods approaches. Topics may include: Applications of AI and machine learning methods in business analytics Network science and social network applications for business Social media analytics Statistics and econometrics in business analytics Use of novel data science techniques in business analytics Robotics and autonomous vehicles Methods and methodologies for business analytics development and deployment Organisational factors in business analytics Responsible use of business analytics and AI Ethical and social implications of business analytics and AI Bias and explainability in analytics and AI Our editorial philosophy is to publish papers that contribute to theory and practice. Journal of Business Analytics is indexed in: AIS eLibrary Australian Business Deans Council (ABDC) Journal Quality List British Library CLOCKSS Crossref Ei Compendex (Engineering Village) Google Scholar Microsoft Academic Portico SCImago Scopus Ulrich's Periodicals Directory

Journal of personality and social psychology Impact Factor 2024-2025 - ResearchHelpDesk - Journal of Personality and Social Psychology publishes original papers in all areas of personality and social psychology and emphasizes empirical reports, but may include specialized theoretical, methodological, and review papers. The journal is divided into three independently edited sections. Attitudes and Social Cognition addresses all aspects of psychology (e.g., attitudes, cognition, emotion, motivation) that take place in significant micro- and macrolevel social contexts. Topics include, but are not limited to, attitudes, persuasion, attributions, stereotypes, prejudice, person memory, motivation and self-regulation, communication, social development, cultural processes, and the interplay of moods and emotions with cognition. We accept papers using traditional social-personality psychology methods. However, we also strongly welcome innovative, theory-driven papers that utilize novel methods (e.g., biological methods, neuroscience, large-scale interventions, social network analyses, or "big data" approaches). Papers that are driven by such methods may be processed under a new category of "Innovations in Social Psychology" and potentially handled in an expedited fashion (see Editorial published on-line). All papers will be evaluated with criteria that are consistent with those of the best empirical outlets in social, behavioral, and biological sciences. Interpersonal Relations and Group Processes focuses on the psychology of (interpersonal, intragroup, intergroup) social relations and relationships, whether enduring or fleeting. Submissions may address one type of social relation (e.g., close romantic relationships) or they may address multiple types of social relation (e.g., status within a team and across an institution). Submissions may employ one method or multiple methods. Submissions may examine one context or multiple contexts (e.g., countries, developmental period). Although a multiplicity of methods and contexts will likely be considered a strength, all submissions should address the implications of the chosen method and context for the power and quality of inference. Abstracting and indexing services providing coverage of Journal of Personality and Social Psychology ABI/INFORM Complete ABI/INFORM Professional Advanced Academic OneFile Academic Search Alumni Edition Academic Search Complete Academic Search Elite Academic Search Index Academic Search Premier American Theological Library Association Religion Database ASSIA: Applied Social Sciences Index & Abstracts Business & Company Profile ASAP Business Source Alumni Edition Business Source Complete Business Source Corporate Business Source Corporate Plus Business Source Elite Business Source Index Business Source Premier Cabell's Directory of Publishing Opportunities in Psychology Chartered Association of Business Schools (CABS) Academic Journal Guide Communication & Mass Media Complete Communication Source Current Abstracts Current Contents: Social & Behavioral Sciences EBSCO MegaFILE Educational Research Abstracts Online ERIH (European Reference Index for the Humanities and Social Sciences) Expanded Academic ASAP Family & Society Studies Worldwide General OneFile Higher Education Abstracts Humanities and Social Sciences Index Retrospective IBZ / IBR (Internationale Bibliographie der Rezensionen Geistes- und Sozialwissenschaftlicher Literatur) InfoTrac Custom International Bibliography of the Social Sciences Journal Citations Report: Social Sciences Edition MasterFILE Complete MasterFILE Elite MasterFILE Premier MEDLINE MLA International Bibliography Mosby's Nursing Consult NSA Collection OCLC OmniFile Full Text Mega Professional ProQuest Central ProQuest Central ProQuest Discovery ProQuest Health Management ProQuest Platinum Periodicals ProQuest Psychology Journals ProQuest Public Health ProQuest Research Library ProQuest Social Science Journals Psychology Collection PsycINFO PsycLine Public Affairs Index Race Relations Abstracts RILM Abstracts of Music Literature SafetyLit SCOPUS Social Sciences Abstracts Social Sciences Citation Index Social Sciences Full Text Social Sciences Index Retrospective Social Services Abstracts Social Work Abstracts SocINDEX SocINDEX with Full Text Sociological Abstracts Sociology Source International Studies on Women and Gender Abstracts TOC Premier Women's Studies International

Theories of innovation often balance contrasting views that either smart people create smart things or smartly constructed institutions create smart things. While population models have shown factors including population size, connectivity, and agent behavior as crucial for innovation, few have taken the individual-central approach seriously by examining the role individuals play within their groups. To explore how network structures influence not only population-level innovation but also performance among individuals, we studied an agent-based model of the Potions Task, a paradigm developed to test how structure affects a group's ability to solve a difficult exploration task. We explore how size, connectivity, and rates of information sharing in a network influence innovation and how these have an impact on the emergence of inequality in terms of agent contributions. We find, in line with prior work, population size has a positive effect on innovation, but that large and small populations perform similarly per capita; that many small groups outperform fewer large groups; that random changes to structure have few effects on innovation; and that the highest performing agents tend to occupy more central network positions. Moreover, we show that every network factor which facilitates innovation leads to a proportional increase in inequality of performance, creating "genius effects" among otherwise "dumb" agents in both idealized and real-world networks. Methods The data presented here were generated from an agent-based model of cultural innovation. Each model is comprised of agents assembled as nodes on a network. The principle model dynamic is elaborated through pairs of agents (dyads) combining sets of items beginning from an initial inventory of six that each agent starts with. Each ideal network is unweighted, but several of the real-world networks (chimpanzee, baboon, and Agta hunter-gatherer) are weighted networks. Items in each agent's inventory are initialized in an array containing two values: the name of the item and the item's score. In order to craft new items, three specific items must be combined between two agents. With the initial set of six items, there are two valid combinations which can be made: a combination of items a1, a2, and a3 or a combination of items b1, b2, and b3. These will form items 1a and 1b, respectively, which can be combined with items from the initial set in order to make further items. Agents select each item based on a probability calculated by dividing each specific item's score by the sum of the scores of all the items in the inventories. Because each novel item discovered is on another "tier" above the set of items used to create it and has a higher score, this creates path dependency in the model (agents are unlikely to go back and use older items in their inventory over new ones). There are four such "tiers" of items which can be discovered and combined and a fifth tier, which is formed by combining each of the two items on the two separate fourth tiers with one another. The specific scores and item combinations are seen in Fig. 1. Each ideal network has a number of state variables which are manipulated. Random networks are initialized as Erdős–Rényi networks with the number of agents and critical edge probability as initial variables, ring networks are initialized with the number of agents as initial variables, and connected cavemen are initialized with the number of cliques and clique size as initial variables. Common to these network structures are the probability of diffusion (or the probability that each individual neighbor of an individual agent which discovers an item receives a new innovation when the focal agent discovers one) and the probability of link alteration, or the probability that each agent has one of its links removed and a new one added at the end of each step in the model.

International Journal of Engineering and Advanced Technology Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. 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Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level

These are the data related to the PLOS ONE paper : Gaumont N, Panahi M, Chavalarias D (2018) Reconstruction of the socio-semantic dynamics of political activist Twitter networks—Method and application to the 2017 French presidential election. PLoS ONE 13(9): e0201879. https://doi.org/10.1371/journal.pone.0201879 This paper proposes an integrated methodology for the data collection, the reconstruction and the visualization of the development of a country political environment from Twitter data. These data cover several aspects of the analysis of the 2017 French presidential campaign election from the perspective of Twitter processing of the Twitter data: intermediary results processed on the tweets dataset (for example text-mining results), additional data from the candidates' programs. Additional information are given in the Supporting information texts.