The theory of affordances

In his Preface the author' says that he started out to review all the more important theories upon the topics ordinarily discussed under human motivation but soon found himself more and more limited to the presentation of his own point of view. This very well characterizes the book. It is a very personal product. It is an outline with some defense of the author's own thinking about instincts and appetites and sentiments and how they function in human behavior. And as the author draws so heavily upon James and McDougall, especially the latter, the book may well be looked upon as a sort of sequel to their efforts. There is a thought-provoking distinction presented between instinct and appetite. An instinct is said to be aroused always by something in the external situation; and, correspondingly, an appetite is said to be aroused by sensations from within the body itself. This places, of course, a heavy emphasis upon the cognitive factor in all instinctive behaviors; and the author prefers to use the cognitive factor, especially the knowledge of that end-experience which will satisfy, as a means of differentiating one instinct from another. In this there is a recognized difference from McDougall who placed more emphasis for differentiation upon the emotional accompaniment. The list of instincts arrived at by this procedure is much like that of McDougall, although the author is forced by his criteria to present the possibility of food-seeking and sex and sleep operating both in the manner of an appetite and also as an instinct. The Shand-McDougall concept of sentiment is taken over and used in the explanation of moral motivation. There is the development within each personality of a sentiment for some moral principle. But this sentiment is not a very powerful motivating factor. It is reinforced by social pressures and by religion, which is treated as an effort of finite man to live in harmony with the infinite reality. Those whose psychological thinking is largely in terms of McDougall will doubtless find this volume a very satisfying expansion; but those who are at all inclined to support their psychological thinking by reference to experimental studies will not be so well pleased. The James-Lange theory, for example, is discussed without mention of the many experimental studies which it has provoked. Theoretical sources appear in general to be preferred to experimental investigations.

Human MotivationThe Mind in Action: A Study of Motives and Values. A. Campbell Garnett

Billions of people participate in online social activities. Most users participate as readers of discussion boards, searchers of blog posts, or viewers of photos. A fraction of users become contributors of user-generated content by writing consumer product reviews, uploading travel photos, or expressing political opinions. Some users move beyond such individual efforts to become collaborators, forming tightly connected groups with lively discussions whose outcome might be a Wikipedia article or a carefully edited YouTube video. A small fraction of users becomes leaders, who participate in governance by setting and upholding policies, repairing vandalized materials, or mentoring novices. We analyze these activities and offer the Reader-to-Leader Framework with the goal of helping researchers, designers, and managers understand what motivates technology-mediated social participation. This will enable them to improve interface design and social support for their companies, government agencies, and non-governmental organizations. These improvements could reduce the number of failed projects, while accelerating the application of social media for national priorities such as healthcare, energy sustainability, emergency response, economic development, education, and more.

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The Reader-to-Leader Framework: Motivating Technology-Mediated Social Participation

Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided annotations and implicit aggregated feedback describing the personal preferences of each user. It is also a common tendency for these systems to encourage the creation of virtual networks among their users by allowing them to establish bonds of friendship and thus provide a novel and direct medium for the exchange of data. We investigate the role of these additional relationships in developing a track recommendation system. Taking into account both the social annotation and friendships inherent in the social graph established among users, items and tags, we created a collaborative recommendation system that effectively adapts to the personal information needs of each user. We adopt the generic framework of Random Walk with Restarts in order to provide with a more natural and efficient way to represent social networks. In this work we collected a representative enough portion of the music social network last.fm, capturing explicitly expressed bonds of friendship of the user as well as social tags. We performed a series of comparison experiments between the Random Walk with Restarts model and a user-based collaborative filtering method using the Pearson Correlation similarity. The results show that the graph model system benefits from the additional information embedded in social knowledge. In addition, the graph model outperforms the standard collaborative filtering method.

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On social networks and collaborative recommendation

Prior research indicates that Facebook usage predicts declines in subjective well-being over time. How does this come about? We examined this issue in 2 studies using experimental and field methods. In Study 1, cueing people in the laboratory to use Facebook passively (rather than actively) led to declines in affective well-being over time. Study 2 replicated these findings in the field using experience-sampling techniques. It also demonstrated how passive Facebook usage leads to declines in affective well-being: by increasing envy. Critically, the relationship between passive Facebook usage and changes in affective well-being remained significant when controlling for active Facebook use, non-Facebook online social network usage, and direct social interactions, highlighting the specificity of this result. These findings demonstrate that passive Facebook usage undermines affective well-being.

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Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence

This disclosure concerns a targeted search within sites/accounts with high cluster focus for a chosen segment The method includes presenting, to a user, a computer interface for specifying one or more search terms for a search query, presenting at least one selectable item corresponding to at least one of an M score and a CFI score filter for the search query, generating an amended search query based on a selected item, and performing a search using the amended search query

System and method for a search engine content filter

Social contagion is the mechanism by which ideas and behaviors spread across human social networks. Simple contagion models approximate the likelihood of adoption as constant with each exposure to an “infected” network neighbor. However, social theory postulates that when adopting an idea or behavior carries personal or social risk, an individual’s adoption likelihood also depends on the number of distinct neighbors who have adopted. Such complex contagions are thought to govern the spread of social movements and other important social phenomena. Online sites, such as Twitter, expose social interactions at a large scale and provide an opportunity to observe the spread of social contagions “in the wild.” Much of the effort in searching for complex phenomena in real world contagions focuses on measuring user adoption thresholds. In this work, we show an alternative method for fitting probabilistic complex contagion models to empirical data that avoids measuring thresholds directly, and our results indicate bias in observed thresholds under both complex and simple models. We also show 1) that probabilistic models of simple and complex contagion are distinguishable when applied to an empirical social network with random user activity; and 2) the predictive power of these probabilistic adoption models against observed adoptions of actual hashtags used on Twitter. We use a set of tweets collected from Nigeria in 2014, focusing on 20 popular hashtags, using the follow graphs of the users adopting the tags during their initial peaks of activ-

Investigating the Observability of Complex Contagion in Empirical Social Networks.

Community based Question and Answer systems have been promoted as web 2.0 solutions to the problem of finding expert knowledge. This promise depends on systems’ capacity to attract and sustain experts capable of offering high quality, factual answers. Content analysis of dedicated contributors’ messages in the Live QnA system found: (1) few contributors who focused on providing technical answers (2) a preponderance of attention paid to opinion and discussion, especially in non-technical threads. This paucity of experts raises an important general question: how do the social affordances of a site alter the ecology of roles found there? Using insights from recent research in online community, we generate a series of expectations about how social affordances are likely to alter the role ecology of online systems.

Whither the Experts? Social Affordances and the Cultivation of Experts in Community Q&A Systems

Social contagion is a subset of contagion which includes all social phenomena that can and do spread via social networks. The notion of how something becomes popular is very relevant to the concept of social contagion. Rumors, fads, and opinions can spread through social networks like wildfire, “infecting” individuals until they become the norm. This thesis investigates the dynamics of social contagion, employing a combination of formal analysis, simulation, and empirical data mining approaches to examine the processes whereby social contagion spreads throughout social networks. I introduce the concept of critical mass for a subclass of social contagion called complex contagion. This concept builds on earlier work to describe the nonlinear dynamics whereby most socially contagious phenomena infect very few people while a few become overwhelmingly popular. I also investigate socially contagious phenomena that arise when rational agents act under conditions of local information. Finally, I examine how my analytic work applies to a large dataset of empirical social contagion and draw implications for further research in the area.

The dynamics of social contagion

Social media sites like Twitter enable users to engage in the spread of contagious phenomena: everything from information and rumors to social movements and virally marketed products. In particular, Twitter has been observed to function as a platform for political discourse, allowing political movements to spread their message and engage supporters, and also as a platform for information diffusion, allowing everyone from mass media to citizens to reach a wide audience with a critical piece of news. Previous work1 suggests that different contagious phenomena will display distinct propagation dynamics, and in particular that news will spread differently through a population than other phenomena. We leverage this theory to construct a system for classifying contagious phenomena based on the properties of their propagation dynamics, by combining temporal and network features. Our system, applicable to phenomena in any social media platform or genre, is applied to a dataset of news-related and political hashtags diffusing through the population of Russian Twitter users. Our results show that news-related hashtags have a distinctive pattern of propagation across the spectrum of Russian Twitter users. In contrast, we find that political hashtags display a number of different dynamic signatures corresponding to different politically active sub-communities. Analysis using ‘chronotopes’ sharpens these findings and reveals an important propagation pattern we call ‘resonant salience.’

Vladimir Barash

Papers

System and method for a search engine content filter

Investigating the Observability of Complex Contagion in Empirical Social Networks.

Whither the Experts? Social Affordances and the Cultivation of Experts in Community Q&A Systems

The dynamics of social contagion

Salience vs. commitment: dynamics of political hashtags in Russian Twitter