Group consensus in social influence:type of consensus information as a moderator of majority and minority influence

Three experiments investigated the effect of consensus information on majority and minority influence. Experiment 1 examined the effect of consensus expressed by descriptive adjectives (large vs. small) on social influence. A large source resulted in more influence than a small source, irrespective of source status (majority vs. minority). Experiment 2 showed that large sources affected attitudes heuristically, whereas only a small minority instigated systematic processing of the message. Experiment 3 manipulated the type of consensus information, either in terms of descriptive adjectives (large, small) or percentages (82%, 18%, 52%, 48%). When consensus was expressed in terms of descriptive adjectives, the findings of Experiments 1 and 2 were replicated (large sources were more influential than small sources), but when consensus was expressed in terms of percentages, the majority was more influential than the minority, irrespective of group consensus.

Non sexist-translation and/in social change: gender issues in translation

Following centuries of feminist struggle, centuries which have born witness to the close relationship between linguistic discrimination and social reality, there is a growing tendency in modern society to acknowledge the vital role played by language in overcoming gender discrimination. Political institutions are currently compensating by instituting the use of non-sexist language through legislative guidelines, and this makes an important contribution to social reform for equality between the sexes. Seeing that translation is so important for the creation of the collective identities on which modern global society depends, it is clear that non-sexist translation is crucial if there is to be non-sexist language. In this article I examine the potential of non-sexist translation in the struggle for gender equality from a both a theoretical and a practical viewpoint, and I end with a critical evaluation of non-sexist translation methods.

The effects of new technology on employment structures in the service sector

This thesis explores the interrelationships between the labour process, the development of technology and patterns of gender differentiation. The introduction of front office terminals into building society branches forms the focus of the research. Case studies were carried out in nine branches, three each from three building societies. Statistical data for the whole movement and a survey of ten of the top thirty societies provided the context for the studies. In the process of the research it became clear that it was not technology itself but the way that it was used, that was the main factor in determining outcomes. The introduction of new technologies is occurring at a rapid pace, facilitated by continuing high growth rates, although front office technology could seldom be cost justified. There was great variety between societies in their operating philosophies and their reasons for and approach to computerisation, but all societies foresaw an ultimate saving in staff. Computerisation has resulted in the deskilling of the cashiering role and increased control over work at all stages. Some branch managers experienced a decrease in autonomy and an increase in control over their work. Subsequent to this deskilling there has been a greatly increased use of part time staff which has enabled costs to be reduced. There has also been a polarisation between career and non-career staff which, like the use of part time staff, has occurred along gender lines. There is considerable evidence that societies' policies, structures and managerial attitudes continue to directly and indirectly discriminate against women. It is these practices which confine women to lower grades and ensure their dependence on the family and which create the pool of cheap skilled labour that societies so willingly exploit by increasing part time work. Gender strategies enter management strategies throughout the operations of the organisation.

State-of-the-art in product-service systems

A Product-Service System (PSS) is an integrated combination of products and services. This Western concept embraces a service-led competitive strategy, environmental sustainability, and the basis to differentiate from competitors who simply offer lower priced products. This paper aims to report the state-of-the-art of PSS research by presenting a clinical review of literature currently available on this topic. The literature is classified and the major outcomes of each study are addressed and analysed. On this basis, this paper defines the PSS concept, reports on its origin and features, gives examples of applications along with potential benefits and barriers to adoption, summarizes available tools and methodologies, and identifies future research challenges.

The representation of food in social media forum Twitter

Social Media is becoming an increasingly important part of people’s lives and is being used increasingly in the food and agriculture sector. This paper considers the extent to which each section of the food supply chain is represented in Twitter and use the hashtag #food. We looked at the 20 most popular words for each part of the supply chain by categorising 5000 randomly selected tweets to different sections of the food chain and then analysing each category. We sorted the users by those who tweeted most frequently and categorised their position in the food supply chain. Finally to consider the indegree of influence, we took the top 100 tweeters from the previous list and consider what following these users have. From this we found that consumers are the most represented area of the food chain, and logistics is the least represented. Consumers had 51.50% of the users and 87.42% of the top words tweeted from that part of the food chain. We found little evidence of logistics representation for either tweets or users (0.84% and 0.35% respectively). The top users were found to follow a high percentage of their own followers with most having over 70% the same. This research will bring greater understanding of how people perceive the food sector and how Twitter can be used within this sector.

Real-time detection, tracking, and monitoring of automatically discovered events in social media

We introduce ReDites, a system for realtime event detection, tracking, monitoring and visualisation. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. Events are automatically detected from the Twitter stream. Then those that are categorised as being security-relevant are tracked, geolocated, summarised and visualised for the end-user. Furthermore, the system tracks changes in emotions over events, signalling possible flashpoints or abatement. We demonstrate the capabilities of ReDites using an extended use case from the September 2013 Westgate shooting incident. Through an evaluation of system latencies, we also show that enriched events are made available for users to explore within seconds of that event occurring.

Who you are or whom you know? Consumption interdependences in social networks

This paper presents an analysis of whether a consumer's decision to switch from one mobile phone provider to another is driven by individual consumer characteristics or by actions of other consumers in her social network. Such consumption interdependences are estimated using a unique dataset, which contains transaction data based on anonymized call records from a large European mobile phone carrier to approximate a consumer's social network. Results show that network effects have an important impact on consumers' switching decisions: switching decisions are interdependent between consumers who interact with each other and this interdependence increases in the closeness between two consumers as measured by the calling data. In other words, if a subscriber switches carriers, she is also affecting the switching probabilities of other individuals in her social circle. The paper argues that such an approach is of high relevance to both switching of providers and to the adoption of new products. © 2013 Copyright Taylor and Francis Group, LLC.

Frontline employees' collaboration in industrial service innovation:routes of co-creation's effects on new service performance

From a Service-Dominant Logic (S-DL) perspective, employees constitute operant resources that firms can draw to enhance the outcomes of innovation efforts. While research acknowledges that frontline employees (FLEs) constitute, through service encounters, a key interface for the transfer of valuable external knowledge into the firm, the range of potential benefits derived from FLE-driven innovation deserves more investigation. Using a sample of knowledge intensive business services firms (KIBS), this study examines how the collaboration with FLEs along the new service development (NSD) process, namely FLE co-creation, impacts on service innovation performance following two routes of different effects. Partial least squares structural equation modeling (PLS-SEM) results indicate that FLE co-creation benefits the NS success among FLEs and firm’s customers, the constituents of the resources route. FLE co-creation also has a positive effect on the NSD speed, which in turn enhances the NS quality. NSD speed and NS quality integrate the operational route, which proves to be the most effective path to impact the NS market performance. Accordingly, KIBS managers must value their FLEs as essential partners to achieve successful innovation from an internal and external perspective, and develop the appropriate mechanisms to guarantee their effective involvement along the NSD process.

Digital resources and their role in advanced service provision:a VRIN analysis

Purpose: We examine the role of digital resources in the context of advanced service provision to determine their strategic potential. Approach: We conduct a theoretical review of the literature to identify digital resources which we subsequently analyse with regards to their value, rarity, inimitability and non-substitutability (VRIN). Findings: Our analysis shows that the strategic value of the digital resources is unlocked through their complementarity. Value: The research has implications for the management of advanced services and contributes towards the grounding of servitization research in the wider economic and management theory.

Harnessing linked knowledge sources for topic classification in social media

Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.

An empirical study on uncertainty identification in social media context

Uncertainty text detection is important to many social-media-based applications since more and more users utilize social media platforms (e.g., Twitter, Facebook, etc.) as information source to produce or derive interpretations based on them. However, existing uncertainty cues are ineffective in social media context because of its specific characteristics. In this paper, we propose a variant of annotation scheme for uncertainty identification and construct the first uncertainty corpus based on tweets. We then conduct experiments on the generated tweets corpus to study the effectiveness of different types of features for uncertainty text identification. © 2013 Association for Computational Linguistics.

Exploring demographic information in social media for product recommendation

In many e-commerce Web sites, product recommendation is essential to improve user experience and boost sales. Most existing product recommender systems rely on historical transaction records or Web-site-browsing history of consumers in order to accurately predict online users’ preferences for product recommendation. As such, they are constrained by limited information available on specific e-commerce Web sites. With the prolific use of social media platforms, it now becomes possible to extract product demographics from online product reviews and social networks built from microblogs. Moreover, users’ public profiles available on social media often reveal their demographic attributes such as age, gender, and education. In this paper, we propose to leverage the demographic information of both products and users extracted from social media for product recommendation. In specific, we frame recommendation as a learning to rank problem which takes as input the features derived from both product and user demographics. An ensemble method based on the gradient-boosting regression trees is extended to make it suitable for our recommendation task. We have conducted extensive experiments to obtain both quantitative and qualitative evaluation results. Moreover, we have also conducted a user study to gauge the performance of our proposed recommender system in a real-world deployment. All the results show that our system is more effective in generating recommendation results better matching users’ preferences than the competitive baselines.