18,471 research outputs found
Understanding Perceptions of Problematic Facebook Use: When People Experience Negative Life Impact and a Lack of Control
While many people use social network sites to connect with friends and
family, some feel that their use is problematic, seriously affecting their
sleep, work, or life. Pairing a survey of 20,000 Facebook users measuring
perceptions of problematic use with behavioral and demographic data, we
examined Facebook activities associated with problematic use as well as the
kinds of people most likely to experience it. People who feel their use is
problematic are more likely to be younger, male, and going through a major life
event such as a breakup. They spend more time on the platform, particularly at
night, and spend proportionally more time looking at profiles and less time
browsing their News Feeds. They also message their friends more frequently.
While they are more likely to respond to notifications, they are also more
likely to deactivate their accounts, perhaps in an effort to better manage
their time. Further, they are more likely to have seen content about social
media or phone addiction. Notably, people reporting problematic use rate the
site as more valuable to them, highlighting the complex relationship between
technology use and well-being. A better understanding of problematic Facebook
use can inform the design of context-appropriate and supportive tools to help
people become more in control.Comment: CHI 201
Determination of Friendship Intensity between Online Social Network Users Based on Their Interaction
Online social networks (OSN) are one of the most popular forms of modern
communication and among the best known is Facebook. Information about the
connection between users on the OSN is often very scarce. It's only known if
users are connected, while the intensity of the connection is unknown. The aim
of the research described was to determine and quantify friendship intensity
between OSN users based on analysis of their interaction. We built a
mathematical model, which uses: supervised machine learning algorithm Random
Forest, experimentally determined importance of communication parameters and
coefficients for every interaction parameter based on answers of research
conducted through a survey. Taking user opinion into consideration while
designing a model for calculation of friendship intensity is a novel approach
in opposition to previous researches from literature. Accuracy of the proposed
model was verified on the example of determining a better friend in the offered
pair
On Facebook, most ties are weak
Pervasive socio-technical networks bring new conceptual and technological
challenges to developers and users alike. A central research theme is
evaluation of the intensity of relations linking users and how they facilitate
communication and the spread of information. These aspects of human
relationships have been studied extensively in the social sciences under the
framework of the "strength of weak ties" theory proposed by Mark Granovetter.13
Some research has considered whether that theory can be extended to online
social networks like Facebook, suggesting interaction data can be used to
predict the strength of ties. The approaches being used require handling
user-generated data that is often not publicly available due to privacy
concerns. Here, we propose an alternative definition of weak and strong ties
that requires knowledge of only the topology of the social network (such as who
is a friend of whom on Facebook), relying on the fact that online social
networks, or OSNs, tend to fragment into communities. We thus suggest
classifying as weak ties those edges linking individuals belonging to different
communities and strong ties as those connecting users in the same community. We
tested this definition on a large network representing part of the Facebook
social graph and studied how weak and strong ties affect the
information-diffusion process. Our findings suggest individuals in OSNs
self-organize to create well-connected communities, while weak ties yield
cohesion and optimize the coverage of information spread.Comment: Accepted version of the manuscript before ACM editorial work. Check
http://cacm.acm.org/magazines/2014/11/179820-on-facebook-most-ties-are-weak/
for the final versio
Two Types of Social Grooming Methods depending on the Trade-off between the Number and Strength of Social Relationships
Humans use various social bonding methods known as social grooming, e.g. face
to face communication, greetings, phone, and social networking sites (SNS). SNS
have drastically decreased time and distance constraints of social grooming. In
this paper, I show that two types of social grooming (elaborate social grooming
and lightweight social grooming) were discovered in a model constructed by
thirteen communication data-sets including face to face, SNS, and Chacma
baboons. The separation of social grooming methods is caused by a difference in
the trade-off between the number and strength of social relationships. The
trade-off of elaborate social grooming is weaker than the trade-off of
lightweight social grooming. On the other hand, the time and effort of
elaborate methods are higher than lightweight methods. Additionally, my model
connects social grooming behaviour and social relationship forms with these
trade-offs. By analyzing the model, I show that individuals tend to use
elaborate social grooming to reinforce a few close relationships (e.g. face to
face and Chacma baboons). In contrast, people tend to use lightweight social
grooming to maintain many weak relationships (e.g. SNS). Humans with
lightweight methods who live in significantly complex societies use various
social grooming to effectively construct social relationships.Comment: Accepted by Royal Society Open Scienc
Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook
A crucial task in the analysis of on-line social-networking systems is to
identify important people --- those linked by strong social ties --- within an
individual's network neighborhood. Here we investigate this question for a
particular category of strong ties, those involving spouses or romantic
partners. We organize our analysis around a basic question: given all the
connections among a person's friends, can you recognize his or her romantic
partner from the network structure alone? Using data from a large sample of
Facebook users, we find that this task can be accomplished with high accuracy,
but doing so requires the development of a new measure of tie strength that we
term `dispersion' --- the extent to which two people's mutual friends are not
themselves well-connected. The results offer methods for identifying types of
structurally significant people in on-line applications, and suggest a
potential expansion of existing theories of tie strength.Comment: Proc. 17th ACM Conference on Computer Supported Cooperative Work and
Social Computing (CSCW), 201
Resolving Multi-party Privacy Conflicts in Social Media
Items shared through Social Media may affect more than one user's privacy ---
e.g., photos that depict multiple users, comments that mention multiple users,
events in which multiple users are invited, etc. The lack of multi-party
privacy management support in current mainstream Social Media infrastructures
makes users unable to appropriately control to whom these items are actually
shared or not. Computational mechanisms that are able to merge the privacy
preferences of multiple users into a single policy for an item can help solve
this problem. However, merging multiple users' privacy preferences is not an
easy task, because privacy preferences may conflict, so methods to resolve
conflicts are needed. Moreover, these methods need to consider how users' would
actually reach an agreement about a solution to the conflict in order to
propose solutions that can be acceptable by all of the users affected by the
item to be shared. Current approaches are either too demanding or only consider
fixed ways of aggregating privacy preferences. In this paper, we propose the
first computational mechanism to resolve conflicts for multi-party privacy
management in Social Media that is able to adapt to different situations by
modelling the concessions that users make to reach a solution to the conflicts.
We also present results of a user study in which our proposed mechanism
outperformed other existing approaches in terms of how many times each approach
matched users' behaviour.Comment: Authors' version of the paper accepted for publication at IEEE
Transactions on Knowledge and Data Engineering, IEEE Transactions on
Knowledge and Data Engineering, 201
- …