Matching Items (41)

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Decentralized information search

Description

Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint

Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.

Contributors

Agent

Created

Date Created
  • 2013

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Anonymous social networks versus peer networks in restaurant choice

Description

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.

Contributors

Agent

Created

Date Created
  • 2013

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IISS a framework to influence individuals through social signals on a social network

Description

Contemporary online social platforms present individuals with social signals in the form of news feed on their peers' activities. On networks such as Facebook, Quora, network operator decides how that

Contemporary online social platforms present individuals with social signals in the form of news feed on their peers' activities. On networks such as Facebook, Quora, network operator decides how that information is shown to an individual. Then the user, with her own interests and resource constraints selectively acts on a subset of items presented to her. The network operator again, shows that activity to a selection of peers, and thus creating a behavioral loop. That mechanism of interaction and information flow raises some very interesting questions such as: can network operator design social signals to promote a particular activity like sustainability, public health care awareness, or to promote a specific product? The focus of my thesis is to answer that question. In this thesis, I develop a framework to personalize social signals for users to guide their activities on an online platform. As the result, we gradually nudge the activity distribution on the platform from the initial distribution p to the target distribution q. My work is particularly applicable to guiding collaborations, guiding collective actions, and online advertising. In particular, I first propose a probabilistic model on how users behave and how information flows on the platform. The main part of this thesis after that discusses the Influence Individuals through Social Signals (IISS) framework. IISS consists of four main components: (1) Learner: it learns users' interests and characteristics from their historical activities using Bayesian model, (2) Calculator: it uses gradient descent method to compute the intermediate activity distributions, (3) Selector: it selects users who can be influenced to adopt or drop specific activities, (4) Designer: it personalizes social signals for each user. I evaluate the performance of IISS framework by simulation on several network topologies such as preferential attachment, small world, and random. I show that the framework gradually nudges users' activities to approach the target distribution. I use both simulation and mathematical method to analyse convergence properties such as how fast and how close we can approach the target distribution. When the number of activities is 3, I show that for about 45% of target distributions, we can achieve KL-divergence as low as 0.05. But for some other distributions KL-divergence can be as large as 0.5.

Contributors

Agent

Created

Date Created
  • 2014

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Control and data analysis of complex networks

Description

This dissertation treats a number of related problems in control and data analysis of complex networks.

First, in existing linear controllability frameworks, the ability to steer a network from any initiate

This dissertation treats a number of related problems in control and data analysis of complex networks.

First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.

Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.

Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.

At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.

Contributors

Agent

Created

Date Created
  • 2017

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Zazzer: forming friendships on digital social networks

Description

Strong communities are important for society. One of the most important community builders, making friends, is poorly supported online. Dating sites support it but in romantic contexts. Other major social

Strong communities are important for society. One of the most important community builders, making friends, is poorly supported online. Dating sites support it but in romantic contexts. Other major social networks seem not to encourage it because either their purpose isn't compatible with introducing strangers or the prevalent methods of introduction aren't effective enough to merit use over real word alternatives. This paper presents a novel digital social network emphasizing creating friendships. Research has shown video chat communication can reach in-person levels of trust; coupled with a game environment to ease the discomfort people often have interacting with strangers and a recommendation engine, Zazzer, the presented system, allows people to meet and get to know each other in a manner much more true to real life than traditional methods. Its network also allows players to continue to communicate afterwards. The evaluation looks at real world use, measuring the frequency with which players choose the video chat game versus alternative, more traditional methods of online introduction. It also looks at interactions after the initial meeting to discover how effective video chat games are in creating sticky social connections. After initial use it became apparent a critical mass of users would be necessary to draw strong conclusions, however the collected data seemed to give preliminary support to the idea that video chat games are more effective than traditional ways of meeting online in creating new relationships.

Contributors

Agent

Created

Date Created
  • 2011

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Multimodal data fusion as a predictior of missing information in social networks

Description

Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat

Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.

Contributors

Agent

Created

Date Created
  • 2012

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Attention harvesting for knowledge production

Description

This dissertation seeks to understand and study the process of attention harvesting and knowledge production on typical online Q&A communities. Goals of this study include quantifying the attention harvesting and

This dissertation seeks to understand and study the process of attention harvesting and knowledge production on typical online Q&A communities. Goals of this study include quantifying the attention harvesting and online knowledge, damping the effect of competition for attention on knowledge production, and examining the diversity of user behaviors on question answering. Project 1 starts with a simplistic discrete time model on a scale-free network and provides the method to measure the attention harvested. Further, project 1 highlights the effect of distractions on harvesting productive attention and in the end concludes which factors are influential and sensitive to the attention harvesting. The main finding is the critical condition to optimize the attention harvesting on the network by reducing network connection. Project 2 extends the scope of the study to quantify the value and quality of knowledge, focusing on the question answering dynamics. This part of research models how attention was distributed under typical answering strategies on a virtual online Q&A community. The final result provides an approach to measure the efficiency of attention transferred into value production and observes the contribution of different scenarios under various computed metrics. Project 3 is an advanced study on the foundation of the virtual question answering community from project 2. With highlights of different user behavioral preferences, algorithm stochastically simulates individual decisions and behavior. Results from sensitivity analysis on different mixtures of user groups gives insight of nonlinear dynamics for the objectives of success. Simulation finding shows reputation rewarding mechanism on Stack Overflow shapes the crowd mixture of behavior to be successful. In addition, project proposed an attention allocation scenario of question answering to improve the success metrics when coupling with a particular selection strategy.

Contributors

Agent

Created

Date Created
  • 2019

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Don't feed the trolls: needs assessment analysis for heuristic to create rhetorical civility in social media

Description

As an outlet of communication between internet users, digital social media has created opinionated engagement between people that have similar and often contrasting views, just like those in face-to-face communication

As an outlet of communication between internet users, digital social media has created opinionated engagement between people that have similar and often contrasting views, just like those in face-to-face communication (Mckenna & Bargh, 2014). The problem is that these digital conversations occur in a synthetic environment, causing users to develop alternative psychological patterns of engagement (Lauren & Hsieh, 2014), that could potentially push them to inadvertently or unknowingly create and participate in negative social interaction with others. The purpose of this study was to determine and assess the needs of a writing heuristic for social media participants to use in engagement with others to increase coherency, civility, and engagement response in content. Research explored existing literature on engagement behavior in digital social media and computer-mediated communication (CMC) and was then used in qualitative sentiment analysis of business-to-consumer social media environments, aiming to recognize the needs in developing a social media writing heuristic. This research found that such heuristic should prompt and advise users to remove ambiguity within engagement practices, encouraging the implementation of salient social markers and nonverbal cues in text. Social media users should also be prompted to create familiarity with others through the posing of messages in an emotional frame that is aligned with their audience’s emotional attitudes, increasing persuasive argumentation and discussion. As well, users should be prompted to thoroughly understand the issues in discussion and follow dynamics to create productive engagement, while avoiding engagement with negative commentary.

Contributors

Agent

Created

Date Created
  • 2016

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A sociopragmatic study of the congratulation strategies of Saudi Facebook users

Description

The aim in this sociopragmatic study was to identify the linguistic and nonlinguistic types of responses used by Saudi Facebook users in the comments of congratulations on the events of

The aim in this sociopragmatic study was to identify the linguistic and nonlinguistic types of responses used by Saudi Facebook users in the comments of congratulations on the events of happy news status updates on Facebook. People usually express their feelings and emotions positively to others when they have happy occasions. However, the ways of expressing congratulation may vary because the expressive speech act “congratulations” is not the only way to express happiness and share others their happy news, especially on the new social media such as Facebook. The ways of expressing congratulation have been investigated widely in face-to-face communication in many languages. However, this has not yet been studied on Facebook, which lacks prosodic strategies and facial expressions that help to convey feelings, despite a few contributions on studying various expressive speech acts such as compliment, condolences, and wishing, among others. Therefore, a total of 1,721 comments of congratulation were collected from 61 different occasions and analyzed qualitatively and quantitatively by using the frame-based approach to understand the construction of politeness of congratulation on Facebook. The results showed 23 verbal types of responses used by the users; however, the use of “congratulations,” “offer of good wishes,” “praise,” and “statements indicating the situation was warranted” were the most frequently used strategies. The results also showed 100 patterns of verbal compound strategies, but the use of “congratulations” with “offer of good wishes” was the most frequently used compound strategy. In addition, 42 types of emojis were found in the comments and categorized into seven different functions. However, the function of expressing endearment was the most frequently used one. Finally, the results showed that the posts received 31 sharings and 3 types of emoji reactions, such as “like” (Thumbs up), “love” (Beating heart), and “wow” (Surprised face), but the use of “like” was the most frequent emoji reaction to the posts. The explored different ways of expressing congratulation and sharing with others their happy news indicated that the linguistic strategies are not the only way to express happiness on Facebook. Therefore, users employed nonlinguistic strategies to express happiness and intensify their congratulations.

Contributors

Agent

Created

Date Created
  • 2017

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It "breaks down this wall: dualities in journalists' engagement with Twitter followers

Description

Scholars have identified that journalists have a strong occupational identity, leading to ideological conceptions of the rules of the field. However, while journalists are often the first to embrace technological

Scholars have identified that journalists have a strong occupational identity, leading to ideological conceptions of the rules of the field. However, while journalists are often the first to embrace technological change, they often do so in different ways than most people. With the arrival of digital technologies, journalists are often faced with practices that run contrary to long-established ideology, and they often carry traditional practices over to new media. Using the theoretical lens of Giddens’s structuration theory, this research identifies traditional journalism structures that encourage or discourage journalists to interact with their followers on the social network Twitter. Using constant comparative analysis to interpret 23 interviews with contemporary journalists, this study identified multiple dualities between the use of Twitter and traditional newsgathering. It also recognized a cognitive dissonance among journalists who use Twitter. Though they can see advantages to using the platform to engage with followers, particularly other journalists and members of their audience, journalists do not seek out Twitter interaction and often avoid or resist it. Finally, this dissertation suggests three walls that block journalists from engaging in the Internet’s facilitation of personal connectivity, engagement, and a true community forum with followers. Although a wall of objectivity has somewhat been broached by Twitter use, walls of storytelling and routine and traditional news values continue to hold strong.

Contributors

Agent

Created

Date Created
  • 2015