Advertisement Rates Research Articles

A Study on the Presentation and Communication Influence of Shaanxi Regional Culture in Public Service Advertisements from the Perspective of Social Network Analysis

Abstract This paper describes the dynamic propagation process of the influence of public service advertisements (PSAs) using the information dissemination model and proposes a click probability function by modeling the click rate of advertisements, which is solved by a heuristic method. The EPR advertisement recommendation algorithm is selected to simulate the push process of the advertisement, and the experimental performance is analyzed. Analyze the presentation of Shaanxi regional culture and the network mobilization mechanism model of enterprise public service advertisement, predict and analyze the click rate of public service advertisement broadcasting, and emphasize the trust analysis of the audience. Variables such as the number of effective viewing of advertisements, the number of link clicks, the number of likes, and the amount of placement are selected to carry out descriptive analysis and correlation analysis of the effect of PSAs on Shaanxi regional culture. From the correlation coefficient matrix, it can be seen that the correlation coefficients between the explanatory variables take smaller values and are at the level below 0.11, and the number of likes has significant positive correlation coefficients with the indicators of advertisement effect at each stage. Thus it can be verified that the social attributes of advertisements play a positive role in the effect of advertisements.

Personality-mediated speed-accuracy tradeoffs in mating in a 17-year periodical cicada

AbstractThere exists growing evidence that animal personality (consistent between individual differences in behavior) can influence an individual’s fitness. Furthermore, limitations in behavioral plasticity may cause personality-mediated tradeoffs to occur, for example, between speed and accuracy in decision making. We explored whether various measures of personality could predict speed-accuracy tradeoffs in mate selection using Pharaoh cicadas (Magicicada septendecim) and examined the phenotypic traits predicting male mating performance and advertisement rates. We assessed whether male exploration behavior, boldness, and weight could predict a male’s overall copulation attempt rate (the number of attempted copulations with conspecifics of either sex), the number of errors a male made when selecting a mate (the number of same-sex copulation attempts), and male reproductive performance (whether a male successfully copulated with a female). We also assessed whether personality-dependent variation in male advertisement rate (the number of calling song bouts) might underpin the correlation between exploration behavior and mating performance. Although male exploration behavior did not predict male advertisement rate, we found that faster-exploring males exhibited higher overall rates of attempted copulations while also attempting more same-sex copulations, compared to slower-exploring males, suggesting a personality-mediated speed-accuracy tradeoff. Despite making more mate choice errors, however, faster explorers were more likely to successfully copulate with females, compared to slower explorers, indicating that speed may be favored over accuracy in systems where heavily male-biased sex ratios lead to scramble competition. Overall, this work highlights the role of personality in sexual selection and demonstrates that personality can influence speed-accuracy trade-offs in mating.

Intelligent Advertising Design Strategy Based on Internet of Things Technology

With the rapid development of modern economy, the advertising industry is crucial to economic and social development, and information technology has made a significant contribution to the development. Outdoor advertising is not only an important part of a city’s image but also reflects the overall appearance of a city’s economy, politics, and culture. With the emergence of IoT technology, new advertising communication modes are constantly updated. The Internet of Things is at the forefront of information technology and provides a major impetus for the development of the advertising industry today. This paper studies the intelligent advertising design strategy based on the Internet of Things technology, which is a truly responsive advertising communication mode that serves the needs of the audience. Through multisensory interaction design, an effective interaction between people and advertisements can be formed. And it adopts a variety of crawling strategies to analyze the intelligent web advertisement crawler system to collect advertisement data in the Internet. The research results show that the repetition rate of advertisements captured by the best priority strategy is stable at around 25%, and the overall advertising information repetition rate is the lowest.

Chaos in a nonautonomous model for the impact of media on disease outbreak

Social media initiatives educate the public about the tools and strategies necessary to defend themselves from emerging diseases. The effect of media advertisements in combating an infectious disease is explored in the present investigation. The numerical results show that the system destabilizes when the growth rate of media advertisements goes above a certain value. For lower ranges of the rate of distribution of awareness through social media platforms, our system showcases stable endemic state. But as the rate of disseminating awareness surpasses a critical value, the system undergoes a Hopf bifurcation and limit cycle oscillations appear. However, the persistent oscillations are killed out and the system returns to a stable endemic state as the rate of distribution of awareness exceeds another threshold value. Extremely large values of the awareness distribution through media advertisements eradicate the disease from the entire community. Model parameters with significant impacts on the disease prevalence and eradication are identified through sensitivity analysis. We extend our model to encapsulate the seasonal variation in the rate of media advertisements. Sufficient conditions have been derived for which the nonautonomous system exhibits globally attractive positive periodic solution. The nonautonomous system is shown to produce chaotic dynamics under the circumstances of the corresponding autonomous system that exhibits limit cycle oscillations. Overall, our findings deduce that media advertisements play a critical role in raising public awareness and ultimately resulting in the eradication of the disease from the society.

Manufacturing/remanufacturing based supply chain management under advertisements and carbon emissions process

One of the most successful ways to get the word out about a product’s popularity across all types of customers is through advertising. It has a valuable direct influence on increasing product demand. The supply chain model is developed for manufacturer and retailer, where advertisements are dependent on demand. The advertisement rate has been considered a function that has enhanced at a diminishing rate concerning time, although the growth rate slowed. During the manufacturing cycle, the market’s demand is a function of advertisement, and the customer’s demand is a linear function of time. The production rate exceeds the demand rate during manufacturing and remanufacturing; shortages are not faced. It involves a manufacturing/remanufacturing process that quickly delivers consumer products and less waste. To keep the environment clean, the cost of carbon emissions is incorporated into the manufacturer’s and supplier’s holding and degrading costs. The model’s primary purpose is to minimize the overall cost of manufacturing and remanufacturing. The overall cost during the manufacturing cycle is higher than that during the remanufacturing cycle. This study confirms that the increasing cost of advertising provides the continuous increasing value of the total cost. A numerical example is provided, graphical representation and sensitivity analysis determine the function’s behavior and test the model.

MODELING THE CONTROL OF BACTERIAL DISEASE BY SOCIAL MEDIA ADVERTISEMENTS: EFFECTS OF AWARENESS AND SANITATION

Media impact has significant effect on reducing the disease prevalence, meanwhile sanitation and awareness can control the epidemic by reducing the growth rate of bacteria and direct contacts with infected individuals. In this paper, we investigate the impacts of media and sanitation coverage on the dynamics of epidemic outbreak. We observe that the growth rate of social media advertisements carries out a destabilizing role, while the system regains stability if the baseline number of social media advertisements exceeds a certain threshold. The dissemination of awareness among susceptibles first destabilizes and then stabilizes the system. The disease can be wiped out if the baseline level of awareness or the rate of spreading global information about the disease and its preventive measures is too high. We obtain an explicit expression for the basic reproduction number [Formula: see text] and show that [Formula: see text] leads to the total eradication of infection from the region. To capture a more realistic scenario, we construct the forced delay model by seasonally varying the growth rate of social media advertisements and incorporating the time lag involved in reporting of total infective cases to the policy makers. Seasonal pattern in the growth rate of social media advertisements adds complexity to the system by inducing chaotic oscillations. For gradual increase in the delay in reported cases of infected individuals, the nonautonomous system switches finitely many times between periodic and chaotic states.

Dynamics of Infectious Diseases: Local Versus Global Awareness

Public awareness programs may deeply influence the epidemic pattern of a contagious disease by altering people’s perception of risk and individuals behavior during the course of the epidemic outbreak. Regardless of the veracity, social media advertisements are expected to execute an increasingly prominent role in the field of infectious disease modeling. In this paper, we propose a model which portrays the interplay between dissemination of awareness at local and global levels, and prevalence of disease. Our sensitivity results determine the correlations between some epidemiologically important parameters and disease prevalence. The growth rate of broadcasting information through social media is found to destabilize the system through limit cycle oscillations whereas the baseline number of social media advertisements stabilize the system by terminating persistent oscillations. The system first undergoes supercritical Hopf-bifurcation and then subcritical Hopf-bifurcation on gradual increase in dissemination rate of awareness at local/global level. Moreover, the disease is eradicated if the dissemination rates of awareness and baseline number of social media advertisements are too large. We also study the effect of seasonal variation of the growth rate of social media advertisements. Our nonautonomous system generates globally attractive positive periodic solution if the growth rate of social media advertisements lies between certain ranges. However, the global attractivity is affected on enhancement in growth rate of social media advertisements and three-periodic solution is observed. Our findings show that baseline number of social media advertisements and dissemination of awareness at individual as well as community levels play a tremendous role in eliminating the burden of disease. Furthermore, a comparison of the effects of local and global awareness reveals that the latter is more effective in curtailing the disease. We believe these findings may be beneficial to understand the contagion characteristics of real epidemics and help to adopt suitable precautionary measures in the form of nonpharmaceutical interventions.

Advertising Click-Through Rate Prediction Based on CNN-LSTM Neural Network.

In the era of big data information, how to effectively predict and analyze the click-through rate of information advertising is the key for enterprises in various fields to seek returns. The point rate prediction of advertising is one of the core contents of advertising calculation. The traditional shallow prediction model cannot meet the nonlinear relationship of data processing, and the manual processing of data information extraction method is very resource consuming. To solve the above problems, this paper proposes a CNN-LSTM (convolutional neural network-long short-term memory) convolution hybrid neural network algorithm to predict the click-through rate of advertisements. According to the neural network algorithm, the prediction model is constructed, and the effective features are extracted in the process of model establishment, and the prediction analysis is carried out according to the simplified LSTM neural network time serialization features. CNN convolution neural network is used to train the prediction model. This paper analyzes the characteristics of traditional prediction methods and the corresponding solutions and carries out feature learning and prediction model construction for advertising click-through rate prediction. Then, the unknown behavior of advertising users is judged and predicted. The results show that, compared with the single structure network of traditional prediction model, the prediction effect based on CNN-LSTM neural network algorithm has higher accuracy.

Conversion’s forecast model for ADs in social networks

In this paper, the authors evaluate the characteristics of customers. Established interconnected segmentation and consumer targeting. Formulated groups of consumer characteristics, as well as the characteristics themselves, applicable in a digital environment. Based on data analysis, the effectiveness of targeting by behavioral and psychographic characteristics was determined. The authors proposed a model to predict the conversion rate of advertisements through the use of socio-demographic, psychographic, behavioral and geographical characteristics. The reliability of the models was checked for compliance and its testing. The results obtained during testing turned out to be comparable with the predicted ones, which allowed us to conclude that it is possible to predict conversion rates in order to increase the efficiency of resource use, including when promoting goods and services on social networks.

Food and Beverage Advertising to Children and Adolescents on Television: A Baseline Study.

The progressive rise in Canadian child obesity has paralleled trends in unhealthy food consumption. Industry has contributed to these trends through aggressive food and beverage marketing in various media and child settings. This study aimed to assess the extent of food and beverage advertising on television in Canada and compare the frequency of food advertising broadcasted during programs targeted to preschoolers, children, adolescents and adults. Annual advertising from 2018 was drawn from publicly available television program logs. Food and beverage advertisement rates and frequencies were compared by, target age group, television station, month and food category, using linear regression modelling and chi-square tests, in SAS version 9.4. Rates of food and beverage advertising differed significantly between the four target age groups, and varied significantly by television station and time of the year, in 2018. The proportion of advertisements for food and beverage products was significantly greater during preschooler-, child-, and adult-programming [5432 (54%), 142,451 (74%) and 2,886,628 (48%), respectively; p < 0.0001] compared to adolescent-programming [27,268 (42%)]. The proportion of advertisements promoting fast food was significantly greater among adolescent-programming [33,475 (51%), p < 0.0001] compared to other age groups. Legislation restricting food and beverage advertising is needed in Canada as current self-regulatory practices are failing to protect young people from unhealthy food advertising and its potential negative health effects.

SDeepFM: Multi-Scale Stacking Feature Interactions for Click-Through Rate Prediction

For estimating the click-through rate of advertisements, there are some problems in that the features cannot be automatically constructed, or the features built are relatively simple, or the high-order combination features are difficult to learn under sparse data. To solve these problems, we propose a novel structure multi-scale stacking pooling (MSSP) to construct multi-scale features based on different receptive fields. The structure stacks multi-scale features bi-directionally from the angles of depth and width by constructing multiple observers with different angles and different fields of view, ensuring the diversity of extracted features. Furthermore, by learning the parameters through factorization, the structure can ensure high-order features being effectively learned in sparse data. We further combine the MSSP with the classical deep neural network (DNN) to form a unified model named sDeepFM. Experimental results on two real-world datasets show that the sDeepFM outperforms state-of-the-art models with respect to area under the curve (AUC) and log loss.

Modeling the effect of literacy and social media advertisements on the dynamics of infectious diseases.

Education empowers humans and gets them ready to face challenges of life efficiently. Literacy and social media campaigns make people aware of the tools and techniques requisite for protection against the emerging diseases. In this paper, we investigate the combined impacts of literacy and social media on the dynamics of infectious diseases spreading through direct contact. Normalized forward sensitivity indices explore the impacts of parameters on basic reproduction number. We perform global sensitivity analysis for the infective population with respect to some controllable epidemiologically important parameters. If the growth rate of broadcasting informations through social media is very high, the system shows limit cycle oscillations. On the other hand, the baseline number of social media advertisements stabilize the system by evacuating persistent oscillations and ultimately settling the system from stable endemic equilibrium to stable disease-free state. The dissemination of awareness among literate people also suppresses the prevalence of limit cycle oscillations and drives the system to disease-free zone. An extension in model is made by assuming the growth rate of social media advertisements as periodic function of time. The simulation results show that the nonautonomous system showcases periodic as well as higher periodic solutions on the increase in the growth rate of advertisements. Our results evoke that media and education play a tremendous role in mounting awareness among the population leading to elimination of disease in the society.

Impacts of TV and radio advertisements on the dynamics of an infectious disease: A modeling study

TV and radio advertisements are widely acknowledged as important interventions in raising issues of public health care and play promising role to control the infection through propagating awareness among the individuals. In this paper, a nonlinear susceptible‐infected‐susceptible (SIS) model is proposed and analyzed to see the impacts of TV and radio advertisements on the spread of influenza epidemic. In the model formulation, it is assumed that the susceptible individuals contract infection through the direct contact with infected individuals. The information regarding the protection against the disease is propagated via TV and radio advertisements, and their growth rates are assumed to be proportional to the fraction of infected individuals. However, the growth rate of TV advertisements decreases with the increase in number of aware individuals. The information broadcasted through TV and radio advertisements induces behavioral changes among the susceptible individuals, and they form an isolated aware class. The epidemiological feasible equilibria, their stability properties, and direction of bifurcation are discussed. The expression for modified basic reproduction number is obtained. The model analysis shows that the dissemination rate of awareness among susceptible individuals due to TV and radio advertisements and baseline number of TV and radio advertisements have potential to reduce the epidemic peak and, thus, control the spread of infection. Further, the analytical findings are well supported through numerical simulation.

Social Media Advertising Trends in Tourism

Advertising in our days is moving to the social media since consumers are spending more and more time on such platforms that offer very customized information for each user. Facebook, for example, is trying to bring each person the most meaningful content, which means the advertising is ultra-customized based on the user activity and preferences, but this kind of personalisation can easily have an unpleasant side effect. The advertising for touristic destinations can become very complex by using fine-tuned campaigns triggered by user consumption patterns revealed in the digital world. By adding a button like “buy now”, the social media apps can easily integrate important e-commerce features, so the advertising of today is not only about presenting the content but also about instantly buying products and services. This paper highlights the way in which advertising messages emerging social media can quickly have a greatly improved success rate. Research methodology took as its starting point the findings of scientific studies published in the literature, the obtained results being interpreted from the perspective of the authors' personal considerations on the topic of the paper. The conclusions highlight the main trends related to increasing the success rate of advertisements in tourism by using social media and by choosing the most appropriate platforms, advertising methods and buying tools such as augmented and/or virtual reality that allow to experiment in advance a travel package, placing of advertising messages on the platforms with the greatest impact and including the direct purchase options inside the add, so that viewing the message can be immediately followed by the acquisition of the promoted services.

Determination of advertisement control policy for complementary and substitute items for a class inventory problem

The optimal advertisement for complementary and substitute items are formulated to control the demand on defective production assortment inventory system. Here, the advertisement rate is unknown and considered as a control variable. The demand is controlled by stock as well as the advertisement rates. The production rate is stock dependent and vanishes when the stock reaches to its maximum value (which is also called carrying capacity for stock). The rate of defective production is constant and the inventory control problem is developed for infinite time horizon. The asymptotically stable point is also analysed by negative eigenvalue, which is shown graphically. The total profit of the system consisting of the sales proceeds, production cost, inventory holding cost and advertisement cost is formulated as a Pontryagin's optimal control problem for steady state. The effect of discounting/time value of money is also taken into consideration. The model is simulated numerically for two items and the optimum results are presented both in tabular form and graphically. Our results show that a joint optimisation of the inventory and advertisement policy leads to a better system performance and increase the profit.

Determination of advertisement control policy for complementary and substitute items for a class inventory problem

The optimal advertisement for complementary and substitute items are formulated to control the demand on defective production assortment inventory system. Here, the advertisement rate is unknown and considered as a control variable. The demand is controlled by stock as well as the advertisement rates. The production rate is stock dependent and vanishes when the stock reaches to its maximum value (which is also called carrying capacity for stock). The rate of defective production is constant and the inventory control problem is developed for infinite time horizon. The asymptotically stable point is also analysed by negative eigenvalue, which is shown graphically. The total profit of the system consisting of the sales proceeds, production cost, inventory holding cost and advertisement cost is formulated as a Pontryagin's optimal control problem for steady state. The effect of discounting/time value of money is also taken into consideration. The model is simulated numerically for two items and the optimum results are presented both in tabular form and graphically. Our results show that a joint optimisation of the inventory and advertisement policy leads to a better system performance and increase the profit.

Financing the public service broadcasting under European Union law

A protocol annexed to the Amsterdam Treaty, regarding public broadcasting in Member States, provides that Member States are free to fund public service broadcasting as far as it does not affect competition in the European Union to an extent which would be contrary to the common interest. As a result of this condition, the European Commission carries out a proportionality test to check if there is no overcompensation or disproportionate effects of public funding. It nonetheless does so by adopting a global control which considers all public broadcaster programmes as part of the public service remit. Such control is problematic because it does not take into account the distinction between commercial and public service programmes nor the actual quality of programmes. The Commission indeed focuses its control on the advertisement market, making sure that public broadcasters do not take advantage of public funding to lower the price of advertisement rates. The freedom enjoyed by public broadcasters to provide any types of programmes as far as they respect the advertisement market comes out to be contrary to citizen welfare.

Imperfect production inventory model with production rate dependent defective rate and advertisement dependent demand

In this article, an economic production quantity (EPQ) model with imperfect production system and advertisement dependent demand has been presented. The advertisement rate has been assumed to be a function of time which has been increased with respect to time at a decreasing rate i.e., it has grown exponentially with respect to time but rate of growth gradually has decreased. Here, the rate of producing defective units has been followed to be a function of production rate. Also, the produced units have been inspected in order to screen the defective units but the screening rate is less than or equal to the production rate and greater than the demand rate. For the developed EPQ model, the total profit has been maximized to obtain the optimum production rate and production run time in the system. Here, algorithms have been developed for finding the optimal profit of the imperfect production inventory model. Finally, different numerical examples have been considered to illustrate the feasibility of the model taking different special cases in the system and then some sensitivity analyses have been carried out to get the impact of some parameters on the objective function of the model.

Magazine hyped: Trends in tobacco advertising and readership characteristics, 2010–2014

We tracked magazine advertisements for seven tobacco products in U.S. magazines from 2010 to 2014 and examined magazine readership characteristics that are associated with advertising placement in 2014.Advertising data came from Kantar Media's Intelligence and readership data came from a 2014 Experian's nationally representative survey of 4667 adult tobacco users. At magazine level, we aggregated total and product-specific number of advertisements and expenditures by year and calculated readership demographics. We used linear and poisson regression models to examine trends in number of tobacco advertisements and expenditures and readership characteristics associated with number of tobacco advertisements in 2014. Analyses were conducted in 2015.There were 5317 tobacco advertisements with expenditures of $796 million that appeared in 322 magazines during 2010–2014. Cigarette advertisements accounted for 2928 (55%), followed by e-cigarettes (n=862, 16%), and snus (n=534, 10%). Advertisements increased by 2.79ad/year for cigarettes, 1.94ad/year for e-cigarettes, and 0.78ad/year for chewing tobacco (p<0.05). In 2014, number of advertisements was associated with select readership characteristics (p<0.05). For every 10% increase in 18–39year-old readers, advertisement rate increased by 1.48 times for cigarettes, 3.44 times for e-cigarettes, and 2.15 times for chewing tobacco. For every 10% increase in readers who earn ≤$24,999, advertisement rate increased by 1.37 times for cigarettes and 1.70 times for e-cigarettes.Magazine tobacco advertising has increased especially for cigarettes and is targeted toward certain demographic subgroups. Regulating tobacco magazine advertising should be integral to tobacco control policies.

Selective & Secured Code Distribution Approach for Multihop Wireless Sensor Networks

This paper proposes an efficient code distribution approach for multihop wireless sensor networks in heterogeneous environment. Reprogramming a sensor network necessitate to fulfil the changing application requirements, bug fix as it is impractical to reach the node once deployed. We are presenting an efficient code distribution scheme to update the running code in sensors over the air with secure authentication & completion verification. The experimental results shows how proposed approach sdeluge is efficient in terms of significant reduction in average completion & dissemination time, advertisement rate, average energy consumption consequently improvement in lifetime of the network.