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With the expanding popularity of Location-Based Games and the rise of advertising therein, there exists a need to comprehend the impact of Location-Based Game Advertising (LGA). This paper seeks to identify what makes positively affective LGA, leveraging Pokémon GO as a probe. Researchers conducted twenty-seven (n=27) semi-structured interviews with Pokémon GO players to reveal lived experiences regarding LGA. Our findings highlight the following direct implications for LGA: (1) LGA act as a digital billboard, conveying qualitative alongside locative information, and (2) well-received LGA enhances the player's agency. We additionally identify findings that have auxiliary implications to LGA: (3) positive memorability occurs when points of interest match physical reality, and (4) ludic engagement is a mediating factor in the memorability of locations. This research demonstrates that LGA in Location-Based Games is surprisingly well-received. However, developers must provide extra consideration to the player's agency for such techniques to be effective. © 2023 ACM.
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The article identifies the major trends in the functioning of marketing communications sector of the Russian Federation during the COVID-19 pandemic, defining the problems this sector faces and the prospects for its development in terms of overcoming the crisis phenomena in the development of digital technologies. Marketing communications sector of the Russian Federation in the context of its response to negative phenomena associated with the pandemic is considered in the article with the use of a three-level approach, including the types of marketing communications, the segments of marketing communication activities under each selected type, and the communication channels used. The trend analysis is carried out for all the selected areas, the main causes of occurring changes are identified. The promising activity areas for participants of marketing communications sector of the Russian Federation in the pandemic and post-pandemic periods are determined. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In March 2020, the World Health Organization announced the COVID-19 outbreak as a pandemic. Most previous social media related research has been on English tweets and COVID-19. In this study, we collect approximately 1 million Arabic tweets from the Twitter streaming API related to COVID-19. Focussing on outcomes that we believe will be useful for Public Health Organizations, we analyse them in three different ways: identifying the topics discussed during the period, detecting rumours, and predicting the source of the tweets. We use the k-means algorithm for the first goal with k=5. The topics discussed can be grouped as follows: COVID-19 statistics, prayers for God, COVID-19 locations, advise and education for prevention, and advertising. We sample 2000 tweets and label them manually for false information, correct information, and unrelated. Then, we apply three different machine learning algorithms, Logistic Regression, Support Vector Classification, and Naïve Bayes with two sets of features, word frequency approach and word embeddings. We find that Machine Learning classifiers are able to correctly identify the rumour related tweets with 84% accuracy. We also try to predict the source of the rumour related tweets depending on our previous model which is about classifying tweets into five categories: academic, media, government, health professional, and public. Around (60%) of the rumour related tweets are classified as written by health professionals and academics. © ACL 2020.All right reserved.
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During COVID-19, the explosive growth of demand for fresh agricultural products on E-commerce platform has increased the difficulty of maintaining the greenness and freshness in delivery. The traditional cold chain delivery is effective in keeping greenness, but its information asymmetry makes the freshness-keeping activities unable to be regulated, which may lead to the supply chain members giving up their freshness-keeping efforts. Can the blockchain technology effectively solve these problems? We consider a fresh agricultural product supply chain consisting of a supplier and an E-commerce platform (retailer). The retailer is responsible for the wholesale and sales of fresh agricultural products, and determines the blockchain adoption degree and advertising effort. The supplier is responsible for delivering fresh agricultural products to consumers, and determines the greenness investment and freshness-keeping effort. Based on the traditional and blockchain-based fresh agricultural product supply chain, we discuss the dynamic optimization of freshness-keeping effort, advertising effort, and blockchain adoption degree. Results show that the supplier will give up the freshness-keeping effort after receiving the wholesale funds in the traditional fresh agricultural product supply chain, which will naturally worsen the fresh agricultural products. When adopting blockchain technology, the supplier continues to make the freshness-keeping effort in delivery. And five specific settings are proved that blockchain is effective in maintaining freshness. But two other specific settings are determined that it is not suited for adopting blockchain. In addition, compared with the traditional fresh agricultural product supply chain, blockchain adoption can effectively reduce the freshness-keeping effort, advertising investment and goodwill for achieving the same profit margin level, and will not affect the greenness investment decision of the supplier. Our research can provide some insights into the cold chain logistics management of fresh blockchain. © 2022
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Consumer purchasing patterns has been affected by COVID-19 health Crisis. Thus, companies must adapt to this change by focusing on understanding the different variables affecting the post pandemic purchase intentions of consumers. Therefore, the basic objective of this study is the development of an integrated framework to investigate the impact of the colors used for products on online advertisement and the consumer personality on the purchase intention of customers in the context of post pandemic. This study will also focus on highlighting the moderating role of age and gender on the relationship between the three constructs. Data were collected from customers of 53 Moroccan textile companies operating in the E-commerce industry. The data was analyzed, and the theoretical model was validated using Partial least square (PLS) and structural equation model (SEM). The findings show that: the color of the product displayed in the advertisement has a high impact on the purchase intention of consumers;the personality of the consumer impact positively the purchase intention of the consumer, and finally, color of the product displayed on the advertisement has a bigger impact on the purchase intention of young people than old people while age doesn't have any significant impact on the relationship between personality and purchase intention. The contribution of this study is to emphasize the roles of understanding the use of colors in advertising and the personality of the consumer, during the post pandemic, on consumer purchasing intention, for companies to innovate and differentiate their offered advertisements to meet the needs and survive the crisis. © 2022 International Consortium for Electronic Business. All rights reserved.
ABSTRACT
With the emergence of COVID-19 disease worldwide, a market of the products related to this disease formed across the Internet. By the time these goods were in short supply, many uncontrolled Dark Web Marketplaces (DWM) were active in selling these products. At the same time, Dark Web Forums (DWF) became proxies for spreading false ideas, fake news about COVID-19, and advertising products sold in DWMs. This study investigates the activities entertained in the DWMs and DWFs to propose a learning-based model to distinguish them from their related counterparts on the surface web. To this end, we propose a COVID-19 Open Source artificial INTelligence framework (C-OSINT) to automatically collect and classify the activities done in DWMs and DWFs. Moreover, we corporate linguistic and stylistic solutions to leverage the classification performance between the content found in DWMs and DWFs and two surface web sources. Our results show that using syntactic and stylistic representation outperforms the Transformer based results over these domains. © 2022 Copyright for this paper by its authors.
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The incredible growth in available news content has been met with steeply increasing demand for news amongst the general population. The 24/7 news cycle gives people an awareness of events, activities and decisions that may have an impact on them (e.g. the latest updates on the COVID-19 outbreak). Despite the flourish of social networks, recent research suggests radio and especially TV are still the main sources of news for many people. However, unlike in social media, the content aired on radio and TV requires people to listen to every single advertisement and music (for radio) before consuming the next item. For this reason, media monitoring companies have to dedicate considerable amount of resources on processing or manually filtering the advertising content (which is blended with the actual news). Often their clients still receive ads. To mitigate this problem, in this paper, we propose No2Ads, an autoregressive deep convolutional neural network (CNN) model that is trained on over 500 h of human annotated training samples to remove ads and music from broadcast content. No2Ads reached very high performance results in our tests, achieving 97% and 95% in precision and recall on detecting ads/music for radio channels;95% precision and 98% recall for TV channels. Between March to September 2021, across 261 radio and TV channels in Australia and New Zealand, No2Ads has detected and filtered out 22,161 h of all captured broadcast content as either advertisements or music. © 2022, Springer Nature Switzerland AG.
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As a result of the pandemic, many brands were forced to adapt their communication. Among the messages disseminated are those of an emotional, reflective, optimistic and even entertaining nature. This behavior has been analyzed by some authors, calling this adaptation of brand discourse to the reality of an existing crisis as Advertcrisis. The objective of this study is to analyze how KFC, Cinemark and Samsung adapted their communication on Facebook during the COVID-19 crisis. It should be noted that these brands market internationally;however, the study of their communication was based on the social networks they manage in Peru. Therefore, the study is subject to a national market. To do so, a comparative review of the messages before and during the crisis was carried out through a qualitative research based on the case study. The results were contrasted with theoretical reflections, obtaining as a result that the three brands were immersed in the scenario described by the Advertcrisis theory. © 2022 IEEE Computer Society. All rights reserved.
ABSTRACT
During the pandemic, brands have seen the need to create messages with greater authenticity in order to become closer and be more relevant to the consumer. Thus, advertisements on digital platforms during the COVID-19 crisis came to modify their essence and structure, telling stories that involved the subject more and making him the protagonist of the message. Some authors have catalogued this restructuring of the advertising discourse during the crisis as Advertcrisis: a creative line that uses the crisis itself to elaborate messages that promote products and services. There are several categories that have used this formula -such as the banking category-, which used the crisis as a creative line to develop its discourse. For this reason, many messages focused on highlighting concepts such as union, progress or improvement. The objective of this study was to analyze, through in-depth interviews, the perception of men and women about the digital messages that some brands of the banking category developed during the first months of the pandemic. It has been observed how the participants of this research have had a negative perception of these many of the virtual strategies, since these have only been limited to emit empty emotional messages, unrelated to the real problems they were going through. © 2022 IEEE Computer Society. All rights reserved.
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The world of marketing differed a lot after the spread of social networks that created more different models with the consumer and the target audience, and coincided with digital ads that became more powerful by their ability to measure and analyze data among consumers, brands and advertising agencies, and their compatibility with generation Z. Advertising revenue on social media in the first half of 2018 on an annual basis was $ 13.1 billion, and in 2019, it became $ 84 billion. Beyond spending on print ads (Zenith Media, 2020). Solo Facebook: $ 25.56 billion. An increase of 107% compared to 2016. (The Drum, 2020) Advertising spending is expected to increase dramatically in 2020 and global advertising spending will reach $ 605 billion, of which $ 110 billion is on digital advertising in the United States only, making the digital marketing landscape more competitive . At Corona pandemic, online shopping is multiplying This reflects the importance of digital advertising in the modern marketing mix, due to several key factors the growth of this sector, among them the huge and increasing demand, the ratios of adopting the solutions of the Internet and high mobile devices, the high youth population that uses the Internet significantly and smartly, and the large use of social networks, And cross-border e-commerce, and the increase in the number of entrepreneurs. Which made people more resistant to traditional forms of advertising as a result of being exposed to a large number of advertising messages every day, As well as the presence of many factors that lead to the inaccuracy of the questionnaire and opinion polls in a traditional way, such as the inability of the sample members to understand a number of questions due to the presence of strange words or poor formulation of the question. If the questionnaire is paper, a number of copies may be lost through the different transmission methods, so the researcher must provide a number of The most important factor affecting the results is the lack of seriousness of the participants in the questionnaire. Some people may neglect to answer a number of questions inadvertently or intentionally, along with many or long questionnaire questions. The respondent may feel bored and tired. With the possibility of some people understanding a number of questions in the wrong way, Thus, they may answer inaccurate answers which created a constant concern about the usefulness of advertising campaigns and their effectiveness? The characteristics of consumers change with the generation z, which requires advertisers and designers to evaluate their advertising methods to follow more effective marketing concepts that employ modern technology such as deep learning on understanding the consumer behavior of generation Z by advertising social networks, through a scientific system that enables multiple parties to work together to model the neural networks, taking advantage of the ability of optimization algorithms They are used in deep learning that builds on the origin of random gradient to help designers and companies understand not only consumer mindset but also analyze their feelings about brands, and improve their design and promotional tools. © 2022 ACM.
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COVID-19 exposure-notification apps have struggled to gain adoption. Existing literature posits as potential causes of this low adoption: privacy concerns, insufficient data transparency, and the type of appeal - collective- vs. individual-good - used to frame the app. As policy guidance suggests using tailored advertising to evaluate the effects of these factors, we present the first field study of COVID-19 contact tracing apps with a randomized, control trial of 14 different advertisements for CovidDefense, Louisiana's COVID-19 exposure-notification app. We find that all three hypothesized factors - privacy, data transparency, and appeals framing - relate to app adoption, even when controlling for age, gender, and community density. Our results offer (1) the first field evidence supporting the use of collective-good appeals, (2) nuanced findings regarding the efficacy of data and privacy transparency, the effects of which are moderated by appeal framing and potential users' demographics, and (3) field-evidence-based guidance for future efforts to encourage pro-social health technology adoption. © 2022 ACM.
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Location-based advertising (LBA), such as billboards and signage, has long been a direct-to-consumer advertising staple. As locative media such as Location-Based Games (LBG) begins to rise in prominence, digital LDA becomes increasingly appealing. In this paper, we explore the impacts of LBA on small businesses in the LBG Pokémon GO, a lacuna in the literature. We gather participant experience through a collection of 35 semi-structured interviews with businesses leveraging Niantic's sponsored location LBA. These testimonies indicate (1) participant businesses found LBG advertising to be satisfactory, (2) LBG advertising improves brand recognizability for local commerce, and (3) local community is an important factor for success in LBG advertising. These findings indicate future patterns for integrating local businesses into LBG like Pokémon GO, suggesting potential for LBG advertising to assist local businesses. © 2022 ACM.
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The purpose is to effectively analyze the dissemination of public service announcements (PSAs) for the COVID-19 under the Internet medium. Based on the methodological basis of excellent PSAs works, this paper will analyze the communication characteristics of PSAs such as narrative spreading positive energy, government-led public welfare and systematic pandemic prevention and control, put forward the communication innovation methods of Internet new crown pandemic PSAs, and elaborate the strategic thinking of anti-pandemic advertising communication innovation from four aspects, including innovation of communication perspective, innovation of creative thinking, innovation of artistic expression and innovation of media release. © 2021 IEEE.
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The objective of this study is to identify the major strategy used by Peruvian Mypes entrepreneurs in the hardware sector, these being discounts/offers and alliances with other companies;Likewise, through a quantitative study, it was found that the study population considers that the two most influential media for advertising are brochures and radio, the internet being the least used. In the same way, it was found that more than 50% have not managed to position themselves in the market due to the little practice of digital marketing strategies, for this reason their survival is at risk. It is concluded that the impact of the pandemic has been shocking, which is why the implementation of good practices of digital marketing strategies is suggested in order to optimize business performance. © 2022 ACM.
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Drawing from social learning theory and the mobile advertising literature on key performance indicators (KPIs), two experiments examined the influence of peer users' conversion in mobile social commerce. Experiment 1 (N = 211, between-subjects [high vs. low number of “sold items”]) tested the effects of peer users' conversion, operationalized as the number of “sold items” in the seller's profile, on the seller-and-profile-related outcomes. The main effect of peer users' conversion was found such that high conversion induced greater cognitive and affective appraisals, higher seller credibility, a more positive profile attitude, greater perceived entrepreneurial talent of the seller, and stronger social commerce conversion intentions. The mediating effect of social learning (mainly affective appraisal) was found. Experiment 2 (N = 348, 2 [high vs. low number of “sold items”] x 2 [high vs. low “followers”] between-subjects factorial design) showed the interaction effects of the number of “sold items” (seller's sales performance) and the number of “followers” (seller's relationship performance) on cognitive and affective appraisals, seller credibility, and profile attitude. Moderated mediation analyses revealed that peer users' conversion exerts a positive impact on the outcome variables through cognitive and affective appraisals when the number of followers is high but not when it is low. © 2022 Elsevier Ltd
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The spread of an infectious disease through a population can be modeled using a network or a graph. In digital advertising, internet device graphs are graph data sets that organize identifiers produced by mobile phones, PCs, TVs, and tablets as they access media on the internet. Characterized by immense scale, they have become ubiquitous as they enable targeted advertising, content customization and tracking. This paper posits that internet device graphs, in particular those based on IP colocation, can provide utility for contact tracing and predicting and modeling the spread of infectious disease. Starting the week of March 16th, 2020, in the United States, many individuals began to 'shelter-in-place' as schools and workplaces across the nation closed because of the COVID-19 pandemic. This paper quantifies the effect of the shelter-in-place orders on a large scale internet device graph with more than a billion nodes by studying the graph before and after orders went into effect. The structure of the graph suggests behavior least conducive to transmission of infection occurred in the US between April 12th and 19th, 2020. This paper also discusses the utility of device graphs for i) contact tracing, ii) prediction of 'hot spots', iii) simulation of infectious disease spread, and iv) delivery of advertisement-based warnings to potentially exposed individuals. The paper also posits an overarching question: can systems and datasets amassed by entities in the digital ad ecosystem aid in the fight against COVID-19? © 2021 IEEE.