Message Processing Research Articles

Decision-making power enhances investors’ neural processing of persuasive message in partnership investment

Decision-making power enhances investors’ neural processing of persuasive message in partnership investment

The Effects of Numerical Evidence and Message Framing in Communicating Vaccine Efficacy

To examine the effects of numerical evidence and message framing in communicating vaccine efficacy information about infectious diseases, an online experiment presented to U.S. adults different versions of a vaccination promotional message that vary by numerical vaccine efficacy evidence: (low efficacy rate: 60% vs. high efficacy rate: 95%), outcome framing (preventing disease-related infection vs. preventing disease-related severe illness), and gain vs. loss framing, using a factorial between-subjects design. While there was no significant interaction between numerical vaccine efficacy evidence and message framing, findings showed that a higher vaccine efficacy rate increased positive beliefs about vaccination and outcome framing emphasizing infection prevention increased message processing fluency. Given that infectious diseases pose higher risks for severe illness among older adults, follow-up analyses by age showed that only younger adults were sensitive to message framing where outcome framing emphasizing infection prevention increased processing fluency.

Are continuous stop-and-go mixnets provably secure?

This work formally analyzes the anonymity guarantees of continuous stop-and-go mixnets and attempts to answer the titular question. Existing mixnet based anonymous communication protocols that aim to provide provable anonymity guarantees rely on round-based communication models, which requires synchronization among all the nodes and clients that is difficult to achieve in practice. Continuous stop-and-go mixnets (e.g., Loopix and Nym) provide a nice alternative by adding a random delay for each message on every hop independent of all other hops and all other messages. The core anonymization technique of continuous mixnets combined with the fact that the messages are sent by the clients to the mixnet at different times makes it a difficult problem to formally prove security for such mixnet protocols; existing end-to-end analyses for such designs provide only experimental evaluations for anonymity and were lacking a comprehensive formal treatment. We are the first to close that gap and provide a formal analysis. We provide two indistinguishability based definitions (of sender anonymity), namely pairwise unlinkability and user unlinkability, tuned specifically for continuous stop-and-go mixnets. We derive the adversarial advantage as a function of the protocol parameters for the two definitions. We show that there is a fundamental lower bound on the adversarial advantage $\delta$ for pairwise unlinkability; however, strong user unlinkability (negligible adversarial advantage) can be achieved if the users message rate ($\lambda_u$) is proportional to message processing rate ($\lambda$) on the nodes.

Exploring the links between type and content of virtual background use during videoconferencing and videoconference fatigue.

The popularity of remote working in recent years has led to a rise in the use of videoconferencing tools. However, these communication tools have also given rise to a phenomenon known as videoconference fatigue (VF). Using the limited capacity model of motivated mediated message processing and impression management theory as the theoretical framework, this study explores how different types and content of virtual backgrounds in videoconferencing influence people's VF and well-being. A survey of 610 users of videoconferencing tools revealed significant variations in the content and type of virtual backgrounds used during videoconferences. Our findings highlight three main points: first, there is a significant relationship between the use of virtual backgrounds and VF; second, pairwise comparisons showed that the type of virtual background significantly influences the amount of VF experienced by users; third, the content of virtual backgrounds also significantly impacts the level of VF experienced by users. These results suggest that careful selection of virtual backgrounds can mitigate VF and improve user well-being. Theoretical and practical implications are discussed.

Analysis of Textual Complexity in Danish News Articles on Climate Change

Structural linguistic features are often overlooked yet potentially important aspects of journalistic practice. Especially in news reporting on climate change, these features can play a crucial role as the proper use of language is tied to message credibility, processing fluency and knowledge retention, which can positively influence the reader to take more climate action. This article analyzes language use in Danish news articles on climate change using a sample of around 32,000 articles from four different outlet types (quality news, niche papers, tabloids, and public service broadcasters) published from 1990 to 2021. We create a machine-learning model of text complexity covering this concept’s semantic and syntactic dimensions. Our findings confirm expected differences in complexity between news outlets, highlighting tabloid articles as engaging with higher semantic complexity, while quality papers and niche papers exhibit higher syntactic complexity. We observe a significant decrease in semantic complexity and a slight increase in syntactic complexity over time, a trend towards more generic language, and an increased use of pronouns, verbs, and adverbs. Most of these changes can be attributed to the emergence of articles by public service broadcasters. Articles by public service broadcasters are characterised by high syntactic complexity, which we consider problematic due to their popularity among the general public.

Corporate Communication Through Podcasts: The Impact of Voice-Fit and Attention During Listening on Parasocial Interaction with the Host and Persuasive Effects

ABSTRACT Companies increasingly integrate their own podcasts into their communication strategies and are thus using a medium in which the host’s voice is the primary contact point for recipients. Since podcasts are generally listened to either with full concentration or in parallel with other activities, the question arises as to how voice characteristics exert an influence in different attention conditions. A 2 × 2-between-subjects-laboratory-experiment (N = 129) shows that attention, but not voice-fit with the company, increases parasocial interaction (PSI) with the host. However, deeper message processing due to higher PSI leads to negative persuasive effects. Scientific and practical implications of these findings are discussed.

Audiovisual messages may improve the processing of traffic information and driver attention during partially automated driving: An EEG study

Partially autonomous vehicles can help minimize human errors. However, being free from some driving subtasks can result in a low vigilance state, which can affect the driver’s attention towards the road. The present study first tested whether drivers of partially autonomous vehicles would benefit from the addition of auditory versions of the messages presented in variable message signs (VMS), particularly, when they find themselves in a monotonous driving situation. A second aim was to test whether the addition of auditory messages would also produce an indirect effect on the driver’s vigilance, improving performance on other driving subtasks not related to the message processing. Forty-three volunteers participated in a driving simulator study. They completed two tasks: (a) a VMS task, where they had to regain manual control of the car if the VMS message was critical, and (b) a car-following task, where they had to pay attention to the preceding car to respond to occasional brake events. Behavioral and EEG data were registered. Overall, results indicated that the addition of audio messages helped drivers process VMS information more effectively and maintain a higher level of vigilance throughout the driving time. These findings would provide useful information for the development of partially automated vehicles, as their design must guarantee that the driver remains attentive enough to assume control when necessary.

Dosage Effects of Anti-prescription Opioid Risk Narratives, Prescription Opioid Misuse Experience, Risk Perceptions, and Message Processing

Dosage Effects of Anti-prescription Opioid Risk Narratives, Prescription Opioid Misuse Experience, Risk Perceptions, and Message Processing

Assessing inoculation's effectiveness in motivating resistance to conspiracy propaganda in Finnish and United States samples.

This study tested the motivational power of inoculation to foster resistance to conspiracy propaganda (9/11 Truth Movement), comparing inoculation effects across United States and Finnish study participants. We used a 2 inoculation (treatment vs. control) × 2 national culture (American vs. Finnish) independent groups design (N = 319), while examining the effects of motivational threat and thinking modes-analytic vs. intuitive-on the inoculation process. To test the effectiveness of the inoculation strategy, we used an excerpt from a conspiracy film Loose Change as a counterattitudinal attack message. Our results indicated that inoculation was effective at motivating resistance regardless of national culture. Inoculation effects emerged mostly as a direct effect on resistance and two indirect effects wherein motivational threat mediated the relationship between inoculation and resistance as well as inoculation and analytic mode of message processing. Although we found that an increase in analytic mode of processing facilitated resistance and intuitive processing increased conspiracy-theory endorsement, the indirect effects between inoculation and resistance via message processing modes were not significant. Finally, the data revealed national culture differences in analytic mode and cultural-context differences mostly pertaining to the relationships between thinking styles, media literacy, and modes of thinking. These results offer important theoretical implications for inoculation scholarship and suggest viable practical solutions for efforts to mitigate misinformation and conspiratorial beliefs.

How Moral Reframing Enhances Political Persuasion: The Role of Processing Fluency and Self-Affirmation

This study examined the psychological mechanisms underlying the persuasive effects of moral reframing—matching message content to recipients’ core moral foundations—by focusing on processing fluency, message processing depth, and self-affirmation as mediators. An online experiment conducted in South Korea demonstrated that, across two policy issues, moral reframing promoted processing fluency and self-affirmation, thereby enhancing the perceived persuasiveness of policy advocacy messages. Furthermore, self-affirmation increased support for policies advocated by the messages. However, the depth of message processing did not differ between participants who read messages aligned with their moral foundations and those exposed to mismatched messages. In sum, the results suggest that moral reframing enhances persuasion by facilitating reflection on positive self-aspects and intuitive processing, rather than by encouraging deeper processing of the messages.

Falling Vocal Intonation Signals Speaker Confidence and Conditionally Boosts Persuasion.

People are often advised to project confidence with their bodies and voices to convince others. Prior research has focused on the high and low thinking processes through which vocal confidence signals (e.g., fast speed, falling intonation, low pitch) can influence attitude change. In contrast, this research examines how the vocal confidence of speakers operates under more moderate elaboration levels, revealing that falling intonation only benefits persuasion under certain circumstances. In three experiments, we show that falling (vs. rising) vocal intonation at the ends of sentences can signal speaker confidence. Under moderate elaboration conditions, falling (vs. rising) vocal intonation increased message processing, bolstering the benefit of strong over weak messages, increasing the proportion of message-relevant thoughts, and increasing thought-attitude correspondence. In sum, the present work examined an unstudied role of vocal confidence in guiding persuasion, revealing new processes by which vocal signals increase or fail to increase persuasion.

A Reliable Publish–Subscribe Mechanism for Internet of Things-Enabled Smart Greenhouses

Messaging protocols for the Internet of Things (IoT) play a crucial role in facilitating efficient product creation and waste reduction, and in enhancing agricultural process efficiency within the realm of smart greenhouses. Publish–subscribe (pub-sub) systems improve communication between IoT devices and cloud platforms. Nevertheless, IoT technology is required to effectively handle a considerable volume of subscriptions or topic adjustments from several clients concurrently. In addition, subscription throughput is an essential factor of the pub-sub mechanism, as it directly influences the speed at which messages may be sent to subscribers. The primary focus of this paper pertains to a performance assessment of the proposed message categorization architecture for the Message Queue Telemetry Transport (MQTT) broker. This architecture aims to establish a standardized approach to pub-sub topics and generate new topics with various performance characteristics. We also standardize the form of MQTT protocol broker topic categorization and payload based on greenhouse specifications. The establishment of topic classification enhances the operational effectiveness of the broker, reduces data volume, and concurrently augments the number of messages and events transmitted from the greenhouse environment to the central server on a per-second basis. Our proposed architecture is validated across multiple MQTT brokers, including Mosquitto, ActiveMQ, Bevywise, and EMQ X, showing enhanced flexibility, extensibility, and simplicity while maintaining full compatibility with greenhouse environments. Key findings demonstrate significant improvements in performance metrics. The message processing time for the proposed Active MQ broker was increased approximately five-fold across all QoS levels compared to the original. Subscription throughput for the Bevywise MQTT Route 2.0 broker at QoS0 reached 1453.053, compared to 290.610 for the original broker. The number of messages in the Active MQ broker at QoS0 surged from 394.79 to 1973.95. These improvements demonstrate the architecture’s potential for broader IoT applications in pub-sub systems.

Efficiency comparison of message brokers

The aim of the article is to compare three main brokers used in the development of web applications: RabbitMQ, Apache Kafka and Apache Pulsar. To conduct the research, a custom application was created to compare two key metrics in the context of message queue performance. These metrics are: latency and number of processed messages per second. The conducted experiments showed that in scenarios requiring processing of backlogged messages by the broker and in cases of minimizing the impact of the SSL protocol on broker performance, Apache Pulsar proved to be the best solu­tion. In the scenario examining message delivery delays, RabbitMQ turned out to be the best tool, while in the case of examining the stability of message processing in real-time, the best results were achieved with Apache Kafka.

Systemic Means of Persuasion and Argument Evaluation

The paper discusses the role of systemic means of persuasion in argument evaluation. The core class of systemic means of persuasion is regress stoppers, whose fundamental function is to halt the infinite regress of justification by making claims, premises, or overall position expressed in a persuasive message more acceptable to a recipient. The paper explores how systemic means of persuasion contribute to the structure of arguments in the Toulmin model and serve as cues for heuristic processing of persuasive messages. It also presents the results of the stylometric analysis and statistical data on the usage of systemic means of persuasion in three corpora which suggest that systemic means of persuasion constitute strategies independent of the strategy based on explicit argumentation marked by inference indicators.

Message Effectiveness of Fear Appeals in Vaccination Communication Campaigns: A Systematic Review.

This systematic review of 54 cross-disciplinary peer-reviewed causal empirical studies helps public health officials, researchers, and healthcare professionals better comprehend the effects of fear appeals in vaccine promotional campaigns on message processing, persuasion, vaccination attitudes, and vaccination intentions. This review documents inconsistent findings across studies, which it attempts to clarify by considering differences in research designs, sample populations, and outcomes measured. In general, we find that fear appeals increase risk perceptions, message involvement, and vaccination attitudes. However, fear appeals have less influence on vaccination intentions, especially among female and general adult populations or populations from the U.S. and other Western cultures. On the other hand, the effect of fear appeals on vaccination intentions is stronger among student populations and those from China (People's Republic of China and Hong Kong) and other non-Western cultures. Also, fear appeals are less persuasive when promoting COVID-19 vaccines and boosters than they are for other vaccines (e.g., HPV, influenza, MMR). Future research should compare fear appeal effectiveness in messages across vaccines or when combined with other executional elements, such as the endorser or type of evidence provided. Finally, future studies should explore other methodological approaches and measure underexplored message outcomes, such as vaccine uptake behavior, in more naturalistic settings.

FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design

Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive web knowledge has fueled interest in developing LLM-based autonomous agents. While LLMs are efficient in decoding human instructions and deriving solutions by holistically processing historical inputs, transitioning to purpose-driven agents requires a supplementary rational architecture to process multi-source information, establish reasoning chains, and prioritize critical tasks. Addressing this, we introduce FinMem, a novel LLM-based agent framework devised for financial decision-making. It encompasses three core modules: Profiling, to customize the agent's characteristics; Memory, with layered message processing, to aid the agent in assimilating hierarchical financial data; and Decision-making, to convert insights gained from memories into investment decisions. Notably, FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. Its adjustable cognitive span allows for the retention of critical information beyond human perceptual limits, thereby enhancing trading outcomes. This framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. We first compare FinMem with various algorithmic agents on a scalable real-world financial dataset, underscoring its leading trading performance in stocks. We then fine-tuned the agent's perceptual span and character setting to achieve a significantly enhanced trading performance. Collectively, FinMem presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

The media-psychological model of environmental risk perception

The article presents the results of a theoretical analysis on the topic of media-psychological aspects of the perception of environmental risks and the presentation of the author's media psychological model of the impact of media messages on the perception of environmental risks. The presented model examines the processes and stages involved in the initial encounter with environmental risk messages in the media and the further outcomes of their processing which can manifest in information-seeking behaviour. According to the presented model, changes in risk perception are considered a series of stages initiated by attention to information and can continue when information-seeking behaviour is triggered. The main models relied on by the author of this study are the Limited Capacity Model of Motivated Mediated Message Processing to describe media message processing and the Risk Information Search and Processing Model to describe aspects of information-seeking behaviour. Several additional communication models dedicated to the consideration of information behaviour and processing of media messages were also used to describe the processes of mass media influence on the perception of environmental risks. Thus, dual models of information processing and persuasive communication are also considered, including the Heuristic-Systematic Model and the Elaboration Likelihood Model, as well as additional theories examining information-seeking behaviour: the Theory of Motivated Information Management and the Planned Risk Information Seeking Model

Can you picture it? Effects of positive and negative depictions of climate futures on climate action intentions

Media messages about climate change are often negative, depicting dire future consequences if action is not taken. While the fear elicited by such messages may motivate audiences, there is growing evidence that hope is also an important driver of engagement in climate action. We conducted a pre-registered experiment with U.S. adults to examine how depictions of positive and negative climate futures (separately and in combination) impact climate action intentions through emotions, counterarguing, and ability to imagine a positive future. We also examined collective efficacy and government efficacy as moderators. Findings shed light on the under-researched impacts of positive climate messaging, revealing benefits as well as risks. Moreover, results highlight the potential for counterarguing to hinder desirable responses to climate futures messaging, offer insights into effects of messages featuring both positive and negative elements, and point to the importance of audiences’ pre-existing government and collective efficacy beliefs in the processing of climate messages.

Flextory: Flexible Software Factory of IoT Data Consumers.

The success of the Internet of Things (IoT) has driven the development, among others, of many different software architectures for producing, processing, and analyzing heterogeneous data. In many cases, IoT applications share common features, such as the use of a platform or middleware, also known as message broker, that collects and manages data traffic between endpoints. However, in general, data processing is very dependent on the case study (sensors that send temperature data, drones that send images, etc.). Thus, the applications responsible for receiving and processing data, which we call consumers, have to be built ad hoc, since some of their elements have to be specially configured to solve specific needs of the case study. This paper presents Flextory, a software factory tool to make it easier for IoT developers to automatically construct configurable consumer applications, which we call FLEX-consumers. Flextory guides developers through the process of generating Java consumers by selecting some desired features such as, for instance, the particular communication protocol to be used. This way, the developer only has to concentrate on designing the algorithm to process the data. In short, the use of Flextory will result in consumer applications with configurable behavior, namely FLEX-consumers, that can connect to a messaging server (for example RabbitMQ) and process the received messages.

Decentralized deconfliction of aerial robots in high intensity traffic structures

AbstractProjections for future air mobility envisage intensely utilized airspace that does not simply scale up from existing systems with centralized air traffic control. This paper considers the implementation and test of a software and hardware framework for decentralized control of aerial vehicles within intensely used airspace. Up to 10 rotary wing vehicles of maximum all up mass of are flown in an outdoor volume with length scale of with GPS and WiFi connectivity. Flight control is implemented using a Pixhawk 4 flight controller running the PX4 firmware with guidance algorithms run on a separate onboard companion computer. Deconfliction is implemented using a simple elastic repulsion model with a guidance update rate of . Traffic structures are constructed from a path of directed waypoints and associated cross sectional geometry. Junctions are implemented when two paths converge into one or when one path diverges into two. Agents engage with structures through execution of flow, merge and swirl velocity rules. Calibration experiments showed that the worst case latency in agents sharing position information was of the order of made up from delays due to finite guidance update rate, WiFi processing and centralized message processing. A choice of vehicle cruise speed of and conflict radius of provided an acceptable compromise between experiment time efficiency (speed) and spatial efficiency (resolution) within the test volume. Results from recirculating junction experiments show that peak deconfliction activity occurs at the junction node, however biased distribution of agents within a corridor means the peak intensity is pushed ahead of the node. Use of meshed helical junction structures significantly reduces the intensity of conflict at the expense of reduced junction time efficiency.