Questions related to Online Social Networks
The great number of resources existing in academic social networks, and the researchers interacting throughout them, looks to be an unquestionable factor supporting the organization and execution of learning activities. Do you agree? Do you have any particular experience in applying those resources in Education?
We all know the statistics that Facebook is the most popular social network in the world. But which social networks are the most popular on a smaller level (e.g. country or region)?
I am not only interested in statistical evidence but also in your own impression and sense: are there networks or plattforms in your country/region that seem to be more popular than Facebook? If so, do you feel like there is a reason why Facebook is not the most fancied network?
I have started writing an article related to "Narcissism" and its effect on "Social Media". Can anyone suggest a good quality journal where I can submit it. Basically, it will be a systematic literature review paper.
I do not finish my writing yet, so I am not able to share my title or abstract yet.
Social Network Analysis Datasets Needed?
I need the following datasets and/or any datasets that has one or more of the following features.
The datasets should allow interaction among Online social users, recommender systems and Online social network server or in a decentralized systems.
Other static profiles (e.g. interests, locations) that could be preserved by privacy schemes.
Thank you in advance.
I have conducted a data collection campaign with 32 people to build a dataset of smartphone sensors during daily life activities. In addition, I have also obtained information related to several activities performed by the volunteers on Facebook, that is their shared contents (e.g., posts, photos, videos), interactions with other users (e.g., likes, comments), and liked pages.
The collected dataset could be used for different tasks. For example, it can be used to study social interactions, human mobility patterns, and context-aware recommender systems.
Can you suggest a journal or conference where I can publish such a dataset?
Thanks in advance.
I have a number of ongoing researches on adaptive web mining techniques and online social network analysis with applications.
Collaboration with funding support for presentation of research outputs in top conferences, workshops and international journals is highly solicited.
Please you can contact me via firstname.lastname@example.org
We are proposing a projected titled ``Framework for the mitigation of the spread of rumors in Online social networks.'' the main objective of the project is the proposal of a frame work that is able to mitigate the propagation of rumors in online social networks.The project requires several discipline from different field in computer science, where different compounds of project are illustrated in the proposed figure and listed as follows:
Data collection: As in any problem that deals with data mining, machine learning, or artificial intelligent, the data is the primary resource the investigate any problem. Thus, this step is one the first and significant steps in framework. The main objective is to develop method and algorithm to extract data from online social networks. Then, it requires structuring these data in order the facilitate their storage and exploitation.
Rumor detection: This step has the objective to detect rumors that are spreading in OSNs. In order to accomplish this task four steps as distinguishable, which are: Rumor classification, Rumor tracking, Stance Classification, and Veracity classification.
Study and analysis of rumor propagation process main objective is to study the dynamic propagation process of rumors in online social networks. this component highlights the the influence or the impact of different factors on the propagation of the rumors. These factors could be related the human factors such as: human individuals and social behaviors, or factors inherent to the networks structure.
Rumor influence minimization compounds aims to stop the propagation of rumors in online social networks.
If you have interested this project, I sincerely invite you to follow it: https://www.researchgate.net/project/Framework-for-the-mitigation-of-the-spread-of-rumors-in-Online-social-networks.
For more information or further collaboration please visit our website: https://hosniaie.wixsite.com/hosni-aie
Please contact us at :
Any collaboration is welcome in this project, we are looking forward to working with you.
I'm looking for an updated literature on network theory that can be applied to the online context. I want to understand how I can classify the ties between members of a certain virtual community as strong or weak (in both qualitative and quantitative ways). For example, I wonder if strong ties (in the online context) consist necessarily of relationships between relatives or friends, or weak ties consist only of relationships between acquaintances or unknown people. I think it depends on the level of reciprocity or interactivity between actors, but I'm not sure.
Can anyone recommend me a paper on it?
As we know that communities size have power-law distribution. Is there a relationship between power-law distribution of communities size and communities hierarchical structure? Can it be said that communiteis locating the last part of the power-law distribution have a stronger hierarchical structure?
I am interested in the field of experience economy and atmospherics and how can brands use this to leverage their social media marketing efforts.
In practitioner literature they are highlighting the trend of brands designing experiences purposively to be showcased on social media.
For example, restaurants are becoming "instagrammable" to increase the chances of customer taking photos and sharing it on social media.
Firms can design their offline space in a strategic way in order to get visitors motivated to generate user-generated-content and post it on social media, which increases the social media presence of the brand.
Although I have found a vast amount of research on experiences and atmospherics, I have not ben able to find literature related that has identified this specific gap.
Can anybody help me with this?
Does anybody know of any author that might have, even slightly, touched on this topic?
Is for my Master's Dissertation.
Thank you very much for your help.
I need your assistance and constructive criticism to a) evaluate parts of my method which are correct b) find weak points and improve on them.
I am far from an expert on ERGM and my case is rather "special" because I am dealing with a large network (most examples that I found were dealing with relatively smaller networks).
I have a network of 7 million edges and 5 million nodes. Nodes have several quantitative attributes. My main goal is to find if these attributes influence the probability of tie formation and if people with similar values tend to have a higher probability to form relations.
Since the network is too large, I took an uniform independent sample for 26697 nodes. The sampling method is favored by literature (see for example http://www.minasgjoka.com/papers/wosn2012-kurant_coarse-topology.pdf). All of their edges even relations to nodes that were not in the sample were included. The sampled network had 39983 nodes and 67024 edges. Then I built a couple of models and I have their results attached to the text file along with the gof of the last one.
I have several questions regarding my results:
1) Do I have to include network metrics (mutual, kstar, etc) if these do not revolve around my hypotheses? Even if I find any results this will probably be irrelevant to the topic that I am working on.
2) I actually did try to build a model for mutual out of curiosity but got back awful diagnostics for mcmc (even with 100,000 sample and 50000 burnin). Instead of normal plots on the right side of the plots printed by mcmc.diagnostics the plots were truly all over the place.
3) The AIC and BIC seem to be quite high compared to other examples. Does it matter? My suspicion is that this is a result of the size of the network.
4) The gof does not seem to fit the data well in several metrics while it is effective in others up to a level. Given the size of the network I am not sure that I will ever get a proper model that would fit the data exactly. Is this however even relevant? Can I still make assertions about my node attributes affecting the probabilities for tie formation?
There are some existing research works that solve the problem of predicting user visibility in an OSN by suggesting an algorithm. The characteristics of the proposed measure are studied on a real (Twitter) social network as well as a generated Erdos-Renyi random network.
A relationship has been established between the visibility and the topological parameters of the network.
Two major findings are as follows –
1. The visibility of a node is proportional to the number of followers it has
2. The followers of the users have similar follower count as the user himself
In this direction, what is the scope of further research work?
Also, it would be very helpful if I could receive suggestions regarding research ideas in this area of Privacy in OSN as a whole. Thank you!
At Volunteer Science; we build collaboration among scientists from leading research universities (including Harvard University, University of Chicago, Northeastern University, and Northwestern University) to expand the tools available for social and behavioral research.
We would like to see if you/your faculty would be interested in running group experiments in their classes.
The basic idea is the faculty would spend 10-30 min of class time playing a specific game. We can provide some teaching material faculty can use to lead a class discussion.
Our experiments can be working in a social science class, business school class (particularly management, strategy, or industrial/organizational psychology, or computer/information sciences classes focusing on HCI, social data, or networking.
Please let me know if you're interested in knowing more about Volunteer Science.
For more information, please feel free to check out attached document or send me a message or e-mail: email@example.com.
I'm interested in studying the behavior of intruder over popular OSN such as Facebook. Intruder or imposter can be defined as an attacker who illegally uses another authorised user account to perform different activities inside that user profile.
I introduce the new model for information diffusion based on node behaviors in social networks. I simulate the models and find interesting result from it. I want to evaluate it with one formal method and find Interactive Markov Chain. Can I use it to evaluate my model?
On Twitter, given a system that infers interests of English-speaking users from tweets they posted or with which they interacted, is there any method to evaluate the system's output without asking users to do it manually?
For example, the system infers the following interests for the Donald Trump's account: The United States, Hillary Clinton, President of the United States, Election, Bill Clinton, Russia, Barack Obama, CNN, Republican Party, Democratic Party, Florida, etc.
I've made an intercise review about the principal debates on youth in the field of sociology, however I've found just some discussions regarding the importance of the topic for the social sciences, and some reflexions about it. But I still can´t find any current author or school who has a solid theory about it. What are the current theories for childhood and youth studies?
The others variables with which I'd like to study the theme of childood and youth, are the socialization processes, the sub-cultures or values of the youth, the migration and communication, mass media and the social networks.
Thank you in advance!!!
When generating random social network using Watts Strogatz (Small World) model or Barabasi Albert (Preferential Attachment) model. What model configuration do you think the best mimicking real online social network such as Facebook or Twitter ?
Threat classifications and models have been proposed for classifying threats related to information systems. For example,
Islam, T., Manivannan, D., & Zeadally, S. (2016). A Classification and Characterization of Security Threats in Cloud Computing. INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING, 7(1).
Cyber-physical security for smart cars: taxonomy of vulnerabilities, threats, and attacks
Jouini, M., Rabai, L. B. A., & Aissa, A. B. (2014). Classification of security threats in information systems. Procedia Computer Science, 32, 489-496.
Threats Classification: State of the Art
However, none of the them talks about classification of threats related to individuals such as home internet users or students.
My question is can the threat classification proposed for information systems can be used as it is for individuals?
I personally believe it shouldn't be used as human and information systems are different.
I have reviewed various theories like social capital, connectivism, metcalfe's law, already but they don't seem to capture the essence of my study.
Hello everyone, Does anyone know how to measure the use of screen time by young adults? I'm trying to quantify this (TV, cellphones, Facebook, Twitter, etc.) for finding any relationship with food choices, eating patterns, fitness activities, and overall overweight/obesity, etc. Is there a scale of tool that I can use? Thank you in advance.
I'm looking for social news feed datasets that include: news feed posts, users' interactions with these posts, users' profiles, social connections between users, etc.
I need a personality trait scale to measure the extent to which consumers use social networks either actively or passively. Some other related constructs may help!
1. For the analysis of the facebook page, can a researcher use data provided by a commercial social media analytics service?
2. Is there any social media analytics service which is reliable and it's data can be used as secondary data?
In my survey study, I have used three techniques, including the face-to-face, email, and the Facebook invitations. The response rate analysis of the first and the second techniques are already counted, I need a guidance to analysis the Facebook invitations in regard with the number of the questionnaire invitations.
Providing its references is appreciated. Thank you.
I am conducting a research on impact of social networking sites on psychologial well being of adults.
I would like to use away to use Amazon Mechanical Turk for my own survey application, but it seems It is not possible for those who are not resident of USA or don't have USA credit card.
I found some services such as crowdflower, crowdguru.de, smartsheet which use mturk as a ground layer and built upon it and also some other similar platforms such as Cloudcrowd or Samesource..
However, I am not quite sure which one more suits my goal, and what are the limitations for the tasks that we can put on mturk (if there is any limitation)
I really appreciate all your ideas,
I am interested in studying Facebook and its various facets in the Indian context. Any guidance in areas of social media studies is welcome.
I would like to compare network structures for two groups that formed on the same topic but for different reasons. I hypothesize that there will be differences in density and network centralization, but it is the case for both random and empirical networks to differ in these values anyway if they are of different sizes.
One possible solution is bootstrapping subgraphs, but I wonder if there are others that have a stronger theoretical basis for network studies?
I'm looking for close related works about Rumor spreading detection in social networks. For example, we suppose that if a network has initial rumor propagated. how can we detect this rumors as early as possible.
l want to find out if such engagement can have an effect on student retention online
I am working on my doctoral thesis regarding social media effects on political participation. I think about doing a empirical study. I figure out some indpendent variables, i.e., politically use of socia media (searching for news, participating political conversation with others online, online social networking size), also some mediators, i.e., political interest, political efficacy, and dependent variable as political partipation online and offline.
I decided to design some questions measuring the political participation in China. But I can not. I red Political Participation in Beijing by Tianjian Shi and I am still confused somehow. Can anyone recommed some books or papers?
I have a social network of actors and edges and I want to rank the nodes according to their position in the network . I tried the centrality measure based rankings but looking for a better combination of these centrality measures or any new methods /algorithm to rank these nodes according to their importance and position in the networks
Is there any specific theory that provides theoretical foundation for studies regarding the effects of social networking sites like Facebook and Twitter etc?
I am studying a number of empirical networks and will have to find a clear way of illustrating various structures and measures of centrality to an audience that may have very little knowledge of graph theory.
I would like to illustrate the various concepts with a popular model similar to the Medici network, but using a directed preferential growth network. I am not too worried about other structural traits for now (weakly / strongly connected, centralized, decentralized etc.) but it would very nice if it were salient to policy / political scientists or economists. Most ideal would be a communication network.
Any examples would be greatly appreciated. Thanks.
Dear All..! Please tell me if any study available on the social sites user group. Currently, I am working on the impact of brand communication on the different online social sites users and ultimately towards generating purchase intention.
Thanks & Regards
Temporary social media has been identified as a key breakthrough in the coming decade. Platforms such as 'SnapChat', 'SilentCirlce,' are gaining ground in mobile social networks.
I'm very interested in the idea of combining online social networks, communities and other web 2.0 elements with the classic support group or 12-step program ideologies.
Has there been any research done into this? I know StopSmokingCenter.net and their parent company are doing a lot of research into it, and there are a few other sites like IntheRooms.com, as well as Facebook Groups full of people helping each other quit.
Just looking for more information, want to use the web as an option to combat addiction and dependence.
Information interaction is one of the most important issues in web 2. But it does not have a precise definition. From your perspective; define scientists’ information interaction in Web 2.
One of the main reasons to use federated social network sites is the privacy and data distribution. What are some methods to collect all these data in order to do some analysis on them? Something like a web crawler for DOSNs.
My students spend a lot of time on FB. When I asked, "Do you get into FB everyday?"; a student responded, "Every hour, madam".
What are the effects on them that you noted? What is our role as educators, in this matter? (Please share your experiences.)
ResearchGate allow researchers to connect with each other, to share publications and news, to create workgroup and collaborate, and to open discussions. What do you think?
How can an organization effectively use OSN to share and create organizational knowledge in order to enhance business models? What are the effects of OSN on business model components? How does OSN reshape activities, processes, models, environment, platforms and architectures in the business field? Which features and functionalities of OSN support businesses in conducting their economic operations? What are resource-based barriers of using OSN in businesses?
If your research addresses any of the above questions, I would be very happy to receive your research outcomes for possible publication in the Special Issue on Online Social Networking and Its Implications in Business.
It has been observed that on social networks especially Facebook, the posts are related to one's self-projection, which is not a positive use of these kind of sites.
I am currently doing my research on sybil attack. I wish to implement sybilguard algorithm in my work. But I cannot find its source code available anywhere on the internet. If anyone has implemented sybilguard algorithm or any similar algorithm, where can I get its source code instead of reinventing the wheel again?
There are a wide range of blogs describing strategies to increase the reach on Facebook but I am having problem finding peer-reviewed papers on this topic. Are you aware of some peer-reviewed papers about the reach on Facebook?
I can find a lot of approaches to identifying influential members of networks based on structural and behavioural measures. But limited examples of susceptibility to influence. Can anyone suggest useful papers or approaches?
Given that most of us are on at least one SNS (social networking site), do you feel like we've begun to engage in experiences only to upload them and make them known to others? And has the purpose of SNSs reduced us simply broadcasting our experiences, rather than 'social networking'?
My thesis is about researchersˊ information seeking behaviour in social network sites.
Is it ethical to analyze and report on data obtained from public blogs? Does one need permission from the blogger or would using data obtained from a blog be considered the same as analyzing data obtained from a newspaper? I have recently come across a few blogs here in Japan by EFL teachers that write openly and honestly (?) about their teaching experiences. And it has just occurred to me that a wealth of information is out there. Has anyone else used blogs for data?
My PhD research project would like seek to extend the existing research on self-presentation and impression formation in the online context, in particular, within two specific Social Networking Sites (Facebook e Linkedin).
I want to know whether there an online tool exists other than a simulator to evaluate and analyze the realtime performance of a social network?
This is based on an older question of mine a while back but, I need help on tackling independence violation and whether there is any in my specific example.
I need to compare densities and degrees for multiple social networks. To give you an idea of a fictional example:
Team Medal Density Degree Months Coach
A Gold 0.1 0.2 6 AA
B Gold 0.4 0.4 12 AA
C Silver 0.1 0.2 24 BB
Ideally, I would like to make a regression model Medal~Density+Degree+Month. Medal is binary (I don't care about other lower medals).
I want to establish whether I can predict the medal that a team has earned based on their social friend network density and degree (not ego but as a whole for each team). In addition, if the regression works it will assert that density and degree play a role in the chances of getting a higher medal.
Each team has their social network metrics taken on different periods since an initial point (Seen in the Months variable).
The issue that I have with the design:
- social networks have shared nodes between teams (nothing I can do about it).
Is this a violation of the assumption of independence?
I also added the Coach field at the end to discuss on whether that would violate the assumption of independence.
Players in Team A can also play in Team B or C etc.
I have a couple of networks that I need to compare in terms of their metrics. Almost all have isolates and in every case most of their nodes are isolated. The relationship type is based on if individuals exchanged messages with one another.
Under which circumstances (if any) should I delete the isolates and calculate the metrics for only connected nodes?