Celebrity, Influencer, and Brand Endorsement: Processes and Effects

Author(s):  
Kineta Hung

A celebrity is a well-known person who commands public recognition and fascination. Given the prevailing consumption culture, the celebrity often engages in brand endorsement practices, making celebrity endorsement (CE) a major advertising strategy. The major strands of CE research highlight key players: the celebrity, consumer, and endorsed brand. In addition to factors that can be traced directly to the celebrity (e.g., trustworthiness, attractiveness, images), CE research discusses how the celebrity’s match with a product or brand and how the celebrity’s relationship with consumers (both fans and the general public) offers important contingency factors that impact the effects of CE. The emergence of influencers in the 21st century gives rise to a new breed of celebrities on social media. Influencers are ordinary-people-turned-experts who specialize in an area of interest (e.g., lifestyle, food, travel). Without the traditional celebrity’s glamour, they use “authentic” and “similar” strategies in their self-branding efforts. They are passionate, sharing their personal brand usage experiences with and providing contextualized recommendations to consumers; and their relationship with consumers is characterized by trust, intimacy, and dialogue. These practices allow an influencer to address the consumer’s instrumental and relational needs when making purchase decisions, an act that a traditional celebrity is less effective in making happen. The celebrity and influencer illustrate the industry- and socially-constructed star-making processes, respectively. On the one hand, traditional celebrities’ path to fame is supported by networked media and the entertainment system. Influencers, on the other hand, create contents that netizens can pick and choose to like and follow, making their path to fame a socially- constructed process. The star-making industries in the 21st century are embracing big data, AI, and machine-learning algorithms as a new governance to “design” and “manufacture” celebrities. In so doing, they usher in an industry-constructed process that has the power and control at an unprecedented scale. The K-pop stars and virtual influencers thus created and managed have been successful. However, their path to fame raises concerns over institutional governance, regulatory control, and ethics of the celebrity and endorsement businesses as well as the means of cultural production. These issues together render celebrity studies and endorsement research a discipline both interesting and challenging to pursue.

1997 ◽  
Vol 2 (4) ◽  
pp. 356-365 ◽  
Author(s):  
Fouad A-L.H. Abou-Hatab

This paper presents the case of psychology from a perspective not widely recognized by the West, namely, the Egyptian, Arab, and Islamic perspective. It discusses the introduction and development of psychology in this part of the world. Whenever such efforts are evaluated, six problems become apparent: (1) the one-way interaction with Western psychology; (2) the intellectual dependency; (3) the remote relationship with national heritage; (4) its irrelevance to cultural and social realities; (5) the inhibition of creativity; and (6) the loss of professional identity. Nevertheless, some major achievements are emphasized, and a four-facet look into the 21st century is proposed.


2020 ◽  
Vol 23 (4) ◽  
pp. 274-284 ◽  
Author(s):  
Jingang Che ◽  
Lei Chen ◽  
Zi-Han Guo ◽  
Shuaiqun Wang ◽  
Aorigele

Background: Identification of drug-target interaction is essential in drug discovery. It is beneficial to predict unexpected therapeutic or adverse side effects of drugs. To date, several computational methods have been proposed to predict drug-target interactions because they are prompt and low-cost compared with traditional wet experiments. Methods: In this study, we investigated this problem in a different way. According to KEGG, drugs were classified into several groups based on their target proteins. A multi-label classification model was presented to assign drugs into correct target groups. To make full use of the known drug properties, five networks were constructed, each of which represented drug associations in one property. A powerful network embedding method, Mashup, was adopted to extract drug features from above-mentioned networks, based on which several machine learning algorithms, including RAndom k-labELsets (RAKEL) algorithm, Label Powerset (LP) algorithm and Support Vector Machine (SVM), were used to build the classification model. Results and Conclusion: Tenfold cross-validation yielded the accuracy of 0.839, exact match of 0.816 and hamming loss of 0.037, indicating good performance of the model. The contribution of each network was also analyzed. Furthermore, the network model with multiple networks was found to be superior to the one with a single network and classic model, indicating the superiority of the proposed model.


2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Junyi Li ◽  
Huinian Li ◽  
Xiao Ye ◽  
Li Zhang ◽  
Qingzhe Xu ◽  
...  

Abstract Background The prediction of long non-coding RNA (lncRNA) has attracted great attention from researchers, as more and more evidence indicate that various complex human diseases are closely related to lncRNAs. In the era of bio-med big data, in addition to the prediction of lncRNAs by biological experimental methods, many computational methods based on machine learning have been proposed to make better use of the sequence resources of lncRNAs. Results We developed the lncRNA prediction method by integrating information-entropy-based features and machine learning algorithms. We calculate generalized topological entropy and generate 6 novel features for lncRNA sequences. By employing these 6 features and other features such as open reading frame, we apply supporting vector machine, XGBoost and random forest algorithms to distinguish human lncRNAs. We compare our method with the one which has more K-mer features and results show that our method has higher area under the curve up to 99.7905%. Conclusions We develop an accurate and efficient method which has novel information entropy features to analyze and classify lncRNAs. Our method is also extendable for research on the other functional elements in DNA sequences.


2008 ◽  
Vol 7 (1) ◽  
pp. 53-70 ◽  
Author(s):  
Mohammad Amouzadeh

This paper aims to investigate the language used by newspapers in post-revolutionary Iran. More precisely, the paper sets out to analyze how such a language is deployed to represent relevant hegemonic ideologies. The approach adopted for this purpose draws inspiration mainly from critical linguistics, where it is hypothesized that, as far as the pertinent metadiscourse goes, media genres serve to activate and perpetuate social power relations. In keeping with this theoretical stance, the paper argues that socially constructed texts can be said to perform two complementary functions; on the one hand, they shed light on the realities experienced in social life; on the other, they reveal such aspects of those realities as are constructed through the use of language. It is thus in this context that the media language used in the post-revolutionary Iran lends itself to analytical investigation, where the available data reveal the co-existence of three competing discourse processes of ‘Islamization’, ‘Iranian Nationalism’ and ‘Western liberalism’, relating to the third stage development of post-revolutionary Iran.


2021 ◽  
pp. 14-22
Author(s):  
G. N. KAMYSHOVA ◽  

The purpose of the study is to develop new scientific approaches to improve the efficiency of irrigation machines. Modern digital technologies allow the collection of data, their analysis and operational management of equipment and technological processes, often in real time. All this allows, on the one hand, applying new approaches to modeling technical systems and processes (the so-called “data-driven models”), on the other hand, it requires the development of fundamentally new models, which will be based on the methods of artificial intelligence (artificial neural networks, fuzzy logic, machine learning algorithms and etc.).The analysis of the tracks and the actual speeds of the irrigation machines in real time showed their significant deviations in the range from the specified speed, which leads to a deterioration in the irrigation parameters. We have developed an irrigation machine’s control model based on predictive control approaches and the theory of artificial neural networks. Application of the model makes it possible to implement control algorithms with predicting the response of the irrigation machine to the control signal. A diagram of an algorithm for constructing predictive control, a structure of a neuroregulator and tools for its synthesis using modern software are proposed. The versatility of the model makes it possible to use it both to improve the efficiency of management of existing irrigation machines and to develop new ones with integrated intelligent control systems.


Author(s):  
Adrian Deveau

Popular media is a series of appropriations and citations of cultural productions, refurbishing past ideas to fit the mold of the present. Representation of art works and cultural products influence the visibility of the groups who produce for popular culture. While social media and contemporary art allow for the rapid spread of ideas through the internet and advertisements, too often are ideas stolen for profit for large companies by exploiting the artistic integrity of uninitiated groups. Queer culture often appropriates historical methodologies for a reclamation of the past to create representation for the future. Queer artists produce landmark aesthetics in visual culture, shaping contemporary fashion trends and artistic movements in the 21st Century. While appropriation as a methodology is not inherently problematic, exploitation develops when artists are neglected credit for works which are exploited for capitalist gain.The research paper The Golden Age of Stealing: An Analysis of Queer Appropriation and Exploitation in 21st Century Popular Culture analyzes the relationship between the appropriation and exploitation of Queer art, using the 1980’s and 90’s club kids as a platform for queer aesthetic production. The paper outlines the dichotomy between representation of queer peoples in the 1990’s and the aesthetics produced to question popular representations and roles within a western consumer society. Using queer performative theories including utopianism, performativity, and disidentification, the paper distinguishes why the stealing of queer art for profit is inherently dangerous and regressive for the queer community, silencing queer voices and perpetrating a heteronormative narrative of cultural production.


2018 ◽  
Vol 7 (2.32) ◽  
pp. 363 ◽  
Author(s):  
N Rajesh ◽  
Maneesha T ◽  
Shaik Hafeez ◽  
Hari Krishna

Heart disease is the one of the most common disease. This disease is quite common now a days we used different attributes which can relate to this heart diseases well to find the better method to predict and we also used algorithms for prediction. Naive Bayes, algorithm is analyzed on dataset based on risk factors. We also used decision trees and combination of algorithms for the prediction of heart disease based on the above attributes. The results shown that when the dataset is small naive Bayes algorithm gives the accurate results and when the dataset is large decision trees gives the accurate results.  


2018 ◽  
Author(s):  
Jarosław Gryz

The purpose of submitted Article is to indicate the character of the challenges related to migrations, their selected forms and influence on Transatlantic community states security . Thesis stipulates that the phenomenon of migrations in the first half of the 21st century more and more strongly defines the context of social security of states implying Transatlantic bonds and international actions taken or not undertaken in their formula. One can assume that migrations, in addition to political and military as well as economic issues, will be the one of domains of NATO security management. The above-mentioned factors will lead to a change in the character of the relations within the Transatlantic Community. <br>


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Olutosin Taiwo ◽  
Absalom E. Ezugwu

The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.


2020 ◽  
Author(s):  
Xavier Couvelard ◽  
Christophe Messager ◽  
Pierrick Penven ◽  
Phillipe Lattes

Abstract The oceanic circulation south of Africa is characterized by a complex dynamics with a strong variability due to the presence of the Agulhas current and numerous eddies. The area of interest of this paper, is also the location of several natural gas fields under seafloor which are targeted for drilling and exploitation.The complex and powerful ocean currents induce significant issues for ship operations at the surface as well as under the surface for deep sea operations. Therefore, the knowledge of the state of the currents and the ability to forecast them in a realistic manner could greatly enforce the safety of various marine operation. Following this objective an array of HF radar systems was deployed to allow a detailed knowledge of the Agulhas currents and its associated eddy activity. It is shown in this study that 4DVAR assimilation of HF radar allow to represent the surface circulation more realistically. Two kind of experiments have been performed, a one-month analysis and two days forecast. The one-month 4DVAR experiment have been compared to geostrophic currents issued from altimeters and highlight an important improvement of the geostrophic currents. Furthermore, despite the restricted size of the area covered with HF radar, we show that the solution is improved almost in the whole domain, mainly upstream and downstream of the HF radar's covered area. We also show that while benefits of the assimilation on the surface current intensity is significantly reduced in the first 6 hours of the forecast, the correction in direction persists after 48 hours.


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