Introduction: For Love Or Money? Defining Relationships In Law And Life

The article focuses on relationships in the light of law and life. It cites the book “Working Relationships,” by Laura Rosenbury wherein the author points on the importance of social ties at work particularly on the legal dichotomy between intimacy, and production. Ethan Leib affirmed the significance of employment where intimacy is formed. Moreover, Mary Anne Case, author of “Enforcing Bargains in an Ongoing Marriage,” says that courts are unwilling to enforce bargains in an ongoing marriage

Learning user-specific latent influence and susceptibility from information cascades

Predicting cascade dynamics has important implications for understanding information propagation and launching viral marketing. Previous works mainly adopt a pair-wise manner, modeling the propagation probability between pairs of users using n^2 independent parameters for n users. Consequently, these models suffer from severe overfitting problem, specially for pairs of users without direct interactions, limiting their prediction accuracy. Here we propose to model the cascade dynamics by learning two low-dimensional user-specific vectors from observed cascades, capturing their influence and susceptibility respectively. This model requires much less parameters and thus could combat overfitting problem. Moreover, this model could naturally model context-dependent factors like cumulative effect in information propagation. Extensive experiments on synthetic dataset and a large-scale microblogging dataset demonstrate that this model outperforms the existing pair-wise models at predicting cascade dynamics, cascade size, and "who will be retweeted".Comment: from The 29th AAAI Conference on Artificial Intelligence (AAAI-2015

A theoretical analysis of the relationship between social capital and corporate social responsibility: concepts and definitions

The paper studies the relationship between social capital (SC) and Corporate Social Responsibility (CSR) by investigating the idea of a virtuous circle, between the level of SC and the implementation of CSR practices, that fosters socio-economic development by generating social inclusion and social networks based on trust and trustworthiness. Following the literature on SC that stresses its multidimensional character, both a cognitive and a structural idea of SC are considered. The first one essentially refers to the dispositional characters of agents that affect their propensity to behave in different ways. The latter refers to social networks connecting agents. With regard to the concept of CSR, a contractarian approach is adopted and CSR is considered as an extended model of corporate governance, based on the fiduciary duties owed to all the firm’s stakeholders. Among stakeholders, a original distinction between “strong” and “weak” stakeholders is introduced. The key element that allows to distinguish between strong and weak stakeholders concerns the consequences that the break in the relationship with the firm produces both on the stakeholder and on the firm. Both these two categories have made specific investments in the firm. However, strong stakeholders are precious for the firm because they bring in strategic assets. On the contrary, weak stakeholders do not bring strategic assets into the firm and firms have material incentives at defecting in the relationship with them. Considering the notions of cognitive and structural SC, a contractarian approach to CSR and the distinction between weak and strong stakeholders, the paper shows that: a) the level of cognitive SC plays a key role in inducing the firm to adopt and observe CSR practices that respect all the stakeholders; b) the decision of adopting formal instruments of CSR contributes to create cognitive SC that is endogenously determined in the model; c) the level of cognitive SC and the decision of adopting CSR practices creates structural SC in terms of a long term relationship between the firm and the weak and strong stakeholders.Social capital, Corporate Social Responsibility, Social network, Ideal utility, Cooperation, Trust.

Identifying influencers in a social network : the value of real referral data

Individuals influence each other through social interactions and marketers aim to leverage this interpersonal influence to attract new customers. It still remains a challenge to identify those customers in a social network that have the most influence on their social connections. A common approach to the influence maximization problem is to simulate influence cascades through the network based on the existence of links in the network using diffusion models. Our study contributes to the literature by evaluating these principles using real-life referral behaviour data. A new ranking metric, called Referral Rank, is introduced that builds on the game theoretic concept of the Shapley value for assigning each individual in the network a value that reflects the likelihood of referring new customers. We also explore whether these methods can be further improved by looking beyond the one-hop neighbourhood of the influencers. Experiments on a large telecommunication data set and referral data set demonstrate that using traditional simulation based methods to identify influencers in a social network can lead to suboptimal decisions as the results overestimate actual referral cascades. We also find that looking at the influence of the two-hop neighbours of the customers improves the influence spread and product adoption. Our findings suggest that companies can take two actions to improve their decision support system for identifying influential customers: (1) improve the data by incorporating data that reflects the actual referral behaviour of the customers or (2) extend the method by looking at the influence of the connections in the two-hop neighbourhood of the customers