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A group of n (> 1) peers are required to cooperate with each other in distributed applications on P2P overlay networks. A P2P group is distributed without a centralized controller and is scalable and heterogeneous. The purpose of this paper is to discuss how to realize a scalable group in P2P overlay networks.

In a group, messages have to be causally delivered to every peer. In order to realize a scalable group, messages are ordered by taking advantage of linear time (LT) and physical time (PT) since message length is O(1). Here, each peer has to hold information on the accuracy of physical clock of each peer and minimum delay time among every pair of peers. Since the size of the information is O(n²), it is difficult for each peer to hold the information and so the authors discuss a multi‐layered model to reduce the size of group information.

Through the evaluation studies, it is shown how the size of the group information can be reduced in a multi‐layered group compared with a traditional flat group.

In this paper, the authors discuss a multi‐layered group model for a scalable group, to reduce the size of group information; and also order messages by using both the linear time and physical time.

The purpose of this paper is to investigate how Turkish consumers’ attitudes toward grammatical styles of the same nutrition message affect persuasiveness; to determine the consumers’ ability to comply with the nutrition messages and to know possible health benefits of them; and to examine nutrient claims on food packages with information that will help consumers to make healthy diet choices.

A questionnaire, comprising eight different grammatical styles of a nutrition message for each kind of food or food products, is applied to randomly to 207 subjects. Another questionnaire is designed including nutritional messages. Subjects (n = 200) are asked about their frequency of compliance and how this behavior is beneficial to health. In total, 5,200 food products are scanned for nutrition labels on packages in four hypermarkets. All the nutrient claims found are recorded as well as the wording.

There are significant effects of grammatical style on persuasiveness, except for meat products. Subjects report that rhetorical question using “how about” in the third message provokes them most. High proportions of subjects have heard of the written nutrition recommendations before. However subjects’ frequencies of compliance with recommendations are low. The relation between compliance and knowledge scores for message 1, 2, 3 and 4 are significant (p < 0.01 and p < 0.05). Of 5,200 foods scanned, 266 foods are recorded for nutrient claims. Fat claims are the most frequent type of nutrient claims; 71 foods have numerical claims; 179 foods have adjectival claims and 16 have both claims.

There have not been any studies on frequency of application of nutrition labeling, consumer attitudes and knowledge of nutrition messages regarding Turkey.

The purpose of this paper is to provide an intelligent spam filtering method to meet the real‐time processing requirement of the massive short message stream and reduce manual operation of the system.

An integrated framework based on a series of algorithms is proposed. The framework consists of message filtering module, log analysis module and rules handling module, and dynamically filters the short message spam, while generating the filtering rules. Experiments using Java are used to execute the proposed work.

The experiments are carried out both on the simulation model (off‐line) and on the actual plant (on‐line). All experiment data are considered in both normal and spam real short messages. The results show that use of the integrated framework leads to a comparable accuracy and meet the real‐time filtration requirement.

The approach in the design of the filtering system is novel. In addition, implementation of the proposed integrated framework allows the method not only to reduce the computational cost which leads to a high processing speed but also to filter spam messages with a high accuracy.

A recent thread in the DIG_REF listserv addressed the integration of text messaging into mainstream reference service. The purpose of this paper is to expand upon that discussion, pointing out the predominant software used by libraries to handle text message reference questions and the volume of reference traffic generated by text messaging queries.

The paper also addresses the ramifications on staffing of the added traffic in text messaging and how libraries might market text messaging reference services to their patrons.

The paper further discusses the unique nature of text messaging queries and how this affects the reference interview.

The paper is intended for the reference services manager looking to incorporate text messaging into a library's repertoire of reference services.

This study seeks to investigate the changes in stock market behavior between the pre and post internet/message board eras.

The study examines the stock return behavior for a large subset of firms in the S&P 100 both before and after the implementation of the firms' message boards on Yahoo! Finance.

The data shows a significant increase in daily trading volume after a firm's message board was established which suggests that either new investors were drawn to the market or existing investors were induced to trade more frequently. The results also show that daily returns are significantly lower in the post‐message board era and that the market may have become riskier as the variance of these daily returns is significantly higher. These results hold after controlling for market and industry wide events and they are not unique to the stock market bubble of the late 1990s or the NBER‐dated recession of 2001.

This study builds on the work of Asthana and connects it to the message board studies conducted by Tumarkin and Whitelaw, and Antweiler and Frank by considering whether or not the internet in general, and message boards specifically, may have changed the underlying behavior of the stock market. It has important implications for those researchers studying market information efficiency and confirms the importance of studying internet information use by investors.

Presents the Message Assistant system (based on a HyperCard stack), designed by the authors to rank electronic mail messages in a priority order specified by the system user. Messages can be ranked according to the name of sender or even a key word in the message text.

This study aims to examine how consumers perceive the persuasion intent and sincerity of brand messages differently and to what extent the advertised brand sounds opportunistic within the context of a crisis, depending on what the message offers.

In Study 1 (N = 163), the brand messages were manipulated in terms of control (an empathetic claim only), monetary reward (with a discount offer) and cause-related marketing (CRM) conditions. In Study 2 (N = 150), the message effects were replicated using a different product category. In Study 3 (N = 216), the three brand messages were examined under high vs low involvement conditions.

The results revealed a linear decrease in negativity in consumer responses when the brand message offers CRM activity, followed by one that offers a discount. It was also found that the monetary reward message was perceived to have greater persuasion intent and be more opportunistic than other message types under low involvement, whereas such effects disappeared under high involvement. Conversely, the CRM message was perceived to have greater persuasion intent and be more opportunistic under high involvement (vs low).

Amidst the global economic impact and corporate landscape changes, there is limited understanding of consumer responses to crisis-related brand messages. Rooted in the attribution theory and the persuasion knowledge model, this study fills the gap by examining how consumers assess the underlying motives of different message types and perceive brands as taking advantage of the crisis situation.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.

This study aims to examine the role of hope and hate in political leaders’ messages in influencing liberals versus conservatives’ social-distancing behavior during the COVID-19 pandemic. Given the increasing political partisanship across the world today, using the appropriate message framing has important implications for social and public policy.

The authors use two Natural Language Processing (NLP) methods – a pretrained package (HateSonar) and a classifier built to implement our supervised neural network-based model architecture using RoBERTa – to analyze 61,466 tweets by each US state’s governor and two senators with the goal of examining the association between message factors invoking hate and hope and increased or decreased social distancing from March to May 2020. The authors examine individuals’ social-distancing behaviors (the amount of nonessential driving undertaken) using data from 3,047 US counties between March 13 and May 31, 2020, as reported by Google COVID-19 Community Mobility Reports and the New York Times repository of COVID-19 data.

The results show that for conservative state leaders, the use of hate increases nonessential driving of state residents. However, when these leaders use hope in their speech, nonessential driving of state residents decreases. For liberal state leaders, the use of hate displays a directionally different result as compared to their conservative counterparts.

Amid the emergence of new analytic techniques and novel data sources, the findings demonstrate that the use of global positioning systems data and social media analysis can provide valuable and precise insights into individual behavior. They also contribute to the literature on political ideology and emotion by demonstrating the use of specific emotion appeals in targeting specific consumer segments based on their political ideology.

The findings have significant implications for policymakers and public health officials regarding the importance of considering partisanship when developing and implementing public health policies. As partisanship continues to increase, applying the appropriate emotion appeal in messages will become increasingly crucial. The findings can help marketers and policymakers develop more effective social marketing campaigns by tailoring specific appeals given the political identity of the consumer.

Using Neural NLP methods, this study identifies the specific factors linking social media messaging from political leaders and increased compliance with health directives in a partisan population.

This study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.

This study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .

The results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.

The sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.

This study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.

Previous studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.