Social Network Advertising Research Articles

Structural equation modelling of customer attitudes towards social network advertising: a case of Iranian social networking site

Structural equation modelling of customer attitudes towards social network advertising: a case of Iranian social networking site

Scalable influence maximization under independent cascade model

Influence maximization is a fundamental problem that aims at finding a small subset of seed nodes to maximize the spread of influence in social networks. Influence maximization problem plays an important role in viral marketing, which is widely adopted in social network advertising. However, finding an optimal solution is NP hard. A more realistic approach is to find a balanced point between the effectiveness and efficiency. A greedy algorithm and its improvements (including Cost-Effective Lazy Forward (CELF) algorithm) were developed to provide an approximation solution with errors bounded at (1–1/e). But the method still suffers from high computational overhead. In this paper, we analyse the bottleneck of the greedy algorithm and propose a more efficient method to replace the time-consuming part of the greedy algorithm. Then, we design a CascadeDiscount algorithm to solve the influence maximization problem. The experimental results on real-world datasets demonstrate that (1) our CascadeDiscount algorithm maintains a close influence spread to CELF and performs better than two heuristics methods, DegreeDiscountIC and TwoStage; (2) our CascadeDiscount method runs two orders of magnitude faster than CELF over real-world datasets.

Social Networking Sites Addiction and the Effect of Attitude towards Social Network Advertising

Abstract Because of the prevalence of mobile devices, the overuse of social networking sites has become a global phenomenon. Social networking sites (hereafter SNS) give a lot of opportunities for business. First of all, businesses can make advertise their product in an easy way. A lot of SNS users can see companies’ advertisements when they use SNS for a different purpose. For marketing management, attitude for advertising is very important. Because Consumers’ attitude is an important factor in influencing consumers’ purchase intention. Purposes of this study are to (1) identify the effect of habits and perceived ease of use on psychological dependence on SNS; and (2) to explore the relationship between SNS dependence and attitudes toward SNS advertisement. 215 data entries were analyzed through SPSS. Analysis results revealed that social networks have partial impacts on approaches of people who are psychologically bond to these web sites, towards advertisements.

Budget Allocation for Maximizing Viral Advertising in Social Networks

Viral advertising in social networks has arisen as one of the most promising ways to increase brand awareness and product sales. By distributing a limited budget, we can incentivize a set of users as initial adopters so that the advertising can start from the initial adopters and spread via social links to become viral. Despite extensive researches in how to target the most influential users, a key issue is often neglected: how to incentivize the initial adopters. In the problem of influence maximization, the assumption is that each user has a fixed cost for being initial adopters, while in practice, user decisions for accepting the budget to be initial adopters are often probabilistic rather than deterministic. In this paper, we study optimal budget allocation in social networks to maximize the spread of viral advertising. In particular, a concave probability model is introduced to characterize each user’s utility for being an initial adopter. Under this model, we show that it is NP-hard to find an optimal budget allocation for maximizing the spread of viral advertising. We then present a novel discrete greedy algorithm with near optimal performance, and further propose scaling-up techniques to improve the time-efficiency of our algorithm. Extensive experiments on real-world social graphs are implemented to validate the effectiveness of our algorithm in practice. The results show that our algorithm can outperform other intuitive heuristics significantly in almost all cases.

Extracting Influential Nodes in Social Networks on Local Weight Aspect

Studies have shown that influential nodes play an important role in all kinds of dynamic behavior in the complex network. Excavation or recognition of such nodes contributes to the development of application areas such as social network advertising and user interest recommendation. Although some heuristic algorithms such as degree, betweenness, closeness and k-shell (or k-core) can identify influential nodes at the same time, they are disadvantaged in terms of accuracy and time complexity. Based on this, the authors propose a novel local weight index to distinguish the node influence based on the theory of ties strength. This index emphasizes that the node influence is jointly decided by the quantity and quality of the neighbors, and its time complexity is much lower than closeness and betweenness. With the aid of SIR information transmission model, this paper verifies the validity of local weight index.

Comprehending Determinants of Demand: Zimbabwe Tourism Destination Scenario

<p>The study investigated on the most dominant determinants of tourism consumption in Zimbabwe tourism destination. The research design was a QUAL to QUAN sequential mixed method starting with a qualitative research design followed by quantitative research. The qualitative research helped in getting the main determinants of demand using in-depth interviews from managers and experts in the tourism industry. The agreed determinants include disposable income, demographic changes, change in taste and preferences, religion dynamics, globalization, marketing and advertisement, customer knowledge, destination branding, social networks, destination’s own price, price of other destinations and media propaganda. These where then tested for their dominance in the accommodation, travel and resort sectors in Zimbabwe through a quantitative design. The results showed that the most controlling determinants of tourism demand in these three sectors include destination’s own prices, level of disposable income, social network discussions, media propaganda, marketing and advertising. The study recommended a low pricing strategy, extensive marketing and utilization of e-resources in marketing.</p>

On the issue of competitiveness of Russian advertising in social networks

In this article, the author discusses the topical problem associated with the ability to determine the target audience when advertising on social networks, which will improve the competitiveness of advertising using effective approaches and modern tools of statistics and Analytics.

Beliefs and attitudes towards social network advertising: A cross-cultural study of Saudi and Sudanese female students

Abstract The study aims to investigate the possible differences in beliefs and attitudes towards social network advertising that may exist among women in Saudi Arabia and Sudan and specify the factors that influence their attitude towards social network advertising. Data sets of two samples from Saudi Arabia (169) and Sudan (195) were collected using a survey of female students from both countries. A t-test was then applied on the processed data, together with correlation and regression analysis, in order to answer the posited research questions. The results revealed no significant differences in attitude towards social media advertising between the two samples, although significant differences in beliefs about social network advertising were documented. In addition, the results indicate that five of the individual factors are statistically significant: these are prior web experience, entertainment, credibility and social norms for the Saudi sample and informativeness, entertainment, credibility and irritation for the Sudanese sample. This study provides insights for international marketers in terms of attitudes and beliefs towards social network advertising. The results may offer some valuable information that may aspire to improve marketing-related activities aimed at social media users.

Factors affecting attitudes and behavioural intention towards social networking advertising: a case of Facebook users in South Korea

This study examined factors (e.g., ad values and social networking advertising characteristics) influencing consumers' attitudes and behavioural intention towards three types of social networking advertising (SNA) on Facebook – home page ad, social impression ad, and organic impression ad. Findings demonstrate that peer influence had the most significant impacts on attitude and behavioural intention across all types of SNA. The significant interaction term of invasiveness and privacy concern indicates that both attitude and behavioural intention were diminished, particularly when perceived invasiveness and privacy concern were high simultaneously. In addition, results suggest that attitudes towards the ad played a mediating role between SNA characteristics and behavioural intention. Lastly, among the types of SNA, consumers preferred organic impression ads that featured friends' names on their newsfeed more than paid ads located on the sidebar of their Facebook pages.

Consumer Attitudes Toward Social Network Advertising

Little is known about the attitudes that consumers have toward social network advertising. To explore this phenomenon, the authors developed a theoretical framework to explain the antecedents and consequences of social network advertising on online behaviors. Based on survey data, four antecedents and two consequences were examined. Drawing upon the technology acceptance model (TAM), the authors developed and tested a series of hypotheses based on this framework. The analysis confirmed the hypothesized relationships and revealed new paths among some constructs on the model. The article concludes with a discussion of implications for future research.

Predicting the influence of users’ posted information for eWOM advertising in social networks

Many social network websites have been aggressively exploring innovative electronic word-of-mouth (eWOM) advertising strategies using information shared by users, such as posts and product reviews. For example, Facebook offers a service allowing marketers to utilize users’ posts to automatically generate advertisements. The effectiveness of this practice depends on the ability to accurately predict a post’s influence on its readers. For an advertising strategy of this nature, the influence of a post is determined jointly by the features of the post, such as contents and time of creation, and the features of the author of the post. We propose two models for predicting the influence of a post using both sources of influence, post- and author-related features, as predictors. An empirical evaluation shows that the proposed predictive features improve prediction accuracy, and the models are effective in predicting the influence score.

Effects of Pre-Purchase Search Motivation on User Attitudes toward Online Social Network Advertising: A Case of University Students

Since last few years, social media have profoundly changed the ways of social and business communication. Particularly, social network sites (SNSs) have rapidly grown in popularity and number of users globally. They have become the main place for social interaction, discussion and communication. Today, businesses of various types use SNSs for commercial communication. Banner advertising is one of the common methods of commercial communication on SNSs. Advertising is a key source of revenue for many SNSs firms such as Facebook. In fact, the ex- istence of many SNSs owners and advertisers is contingent upon the success of social network advertising (SNA). Users demand free SNS services which makes SNA crucial for SNSs firms. SNA can be effective only if it is aligned with user motivations. Marketing literature identifies pre-purchase search as a primary consumer motivation for using media. The current study aims to identify the effects of pre-purchase search motivation (PSM) on user attitudes toward SNA. It also assesses the association between the attitudes toward SNA and users' banner ad-clicking behavior on SNSs. Data was gathered from 200 university students in Islamabad using offline survey. Results show positive effects of PSM on user attitudes toward SNA. They also show posi- tive association between user attitudes toward SNA and their SNS banner ad-clicking behavior. The firms which promote their products through SNSs to the young South Asian consumers may benefit from the findings of the current study.

Ranked content advertising in online social networks

Online social networks (OSNs) such as Twitter, Digg and Facebook have become popular. Users post news, photos and videos, etc. and followers of such users then view and comment the posted informati...

Effectiveness of Online Advertising on Social Networking Sites - A Case Study on Facebook

The purpose of this dissertation is to investigate and find out the benefits of online advertising on social networking sites such as Facebook in Bangladesh. The mode of advertising and the perspective of Marketing have been changing to reach quick and easily near to customer door. From 1999 to 2012, IAB reports show that the internet advertising revenues hit historically at nearly $9.3 billion. Digital Marketing is a highly effective medium for interacting and engaging to the consumers, through social media consumers play no longer as passive but are more active participants in contemporary online media. The online advertising is an increasingly important component of public relations, organisations use social network sites to build relationships with key publics, provide a variety of organisational information.The proposed study aims to discuss a brief overview of the market of social network advertising and to determine the effectiveness of advertisements on social networking to attract customers. The online business in Bangladesh has just been moving positively where 5 per cent of total population are active internet user and 1.9 per cent of total population are using Facebook (By IWS, September 2012).A qualitative research with case study design has been used to find out the total effectiveness of online advertising on Bangladesh marketing system using of social networking site Facebook. The data have collected from several media, from own website and from Facebook advert page before data been organised by the help of SPSS.The outcomes from this research are not enough to justify the whole scenario of Bangladesh online marketing facilities. A single marketing organisation like bikroy.com has just launch no more than two years.In the recommendations section Bangladesh would be a great area to make any organisation profitable by using of social networking sites like Facebook. Online advertising are getting benefited as the internet user are increasing rapidly in Bangladesh.

Maximizing the performance of advertisements diffusion: A simulation study of the dynamics of viral advertising in social networks

In the era of web2.0, marketers are eager to benefit from viral advertising. In this paper we propose a computational network model of viral advertising to examine the maximization of influence within social networks. For our network model we combine both the independent cascade model and the threshold model. We use a spreading threshold to trigger the cascading process, to examine the ways in which advertisements spread across the social network. We also investigate the procedures for choosing an initial set of people to maximize the performance of advertisement spreading. Furthermore, we analyse the impact of network structures on the dynamics of diffusion, and a strategy for combining viral advertising with mass marketing in e-commerce. We also run simulations using a real dataset to check the diffusion of advertisements in an online social network. Ultimately we discovered that a combination of viral advertising and mass marketing is better to diffuse advertisements than either method wholly by itself. Using an optimal algorithm improves diffusion performance, but using ‘degree’ is also an alternative way of choosing initial nodes when the whole structure of network is unknown. Integrating simulations to build a real-time decision support platform will make the diffusion of advertisements more efficient.

Why we ignore social networking advertising

PurposeThe purpose of this paper is to focus on college students, users of online social networks, as main sources of information that helps advertisers understand the ways in which advertisements are perceived online.Design/methodology/approachResults were reached through qualitative research. Personal in‐depth interviews, utilizing Zaltman Metaphor Elicitation Technique (ZMET), were conducted among 20 college students. Interviews consisted of using screenshots of advertisements in online social networks to uncover respondents' reactions.FindingsIt was generally concluded that the users of online social networks do not dislike advertisements, but they simply do not notice them. Other content found in online social networks mitigates the attractiveness of the advertisements. Hence, the respondents reported that the brand recognition in online social networks was found to be much lower than the one created through other media channels.Practical implicationsAdvertising in online social networks is a major unexplored advertising area. Interactivity on the internet shifts the ways in which users perceive advertising, and whether they perceive it at all. The paper discusses content that catches users' attention and its relation to advertisements.Originality/valueThrough literature review it has been revealed that no similar research exists. The findings of this research will aid advertisers in recognizing the possibility of advertising to the online social networks' population, taking into consideration different needs, and preferences of such users.

Camera Brand Congruence and Camera Model Propagation in the Flickr Social Graph

Given that my friends on Flickr use cameras of brand X, am I more likely to also use a camera of brand X? Given that one of these friends changes her brand, am I likely to do the same? Do new camera models pop up uniformly in the friendship graph? Or do early adopters then “convert” their friends? Which factors influence the conversion probability of a user? These are the kind of questions addressed in this work. Direct applications involve personalized advertising in social networks. For our study, we crawled a complete connected component of the Flickr friendship graph with a total of 67M edges and 3.9M users. 1.2M of these users had at least one public photograph with valid model metadata, which allowed us to assign camera brands and models to users and time slots. Similarly, we used, where provided in a user’s profile, information about a user’s geographic location and the groups joined on Flickr. Concerning brand congruence, our main findings are the following. First, a pair of friends on Flickr has a higher probability of being congruent, that is, using the same brand, compared to two random users (27% vs. 19%). Second, the degree of congruence goes up for pairs of friends (i) in the same country (29%), (ii) who both only have very few friends (30%), and (iii) with a very high cliqueness (38%). Third, given that a user changes her camera model between March-May 2007 and March-May 2008, high cliqueness friends are more likely than random users to do the same (54% vs. 48%). Fourth, users using high-end cameras are far more loyal to their brand than users using point-and-shoot cameras, with a probability of staying with the same brand of 60% vs 33%, given that a new camera is bought. Fifth, these “expert” users’ brand congruence reaches 66% for high cliqueness friends. All these differences are statistically significant at 1%. As for the propagation of new models in the friendship graph, we observe the following. First, the growth of connected components of users converted to a particular, new camera model differs distinctly from random growth. Second, the decline of dissemination of a particular model is close to random decline. This illustrates that users influence their friends to change to a particular new model, rather than from a particular old model. Third, having many converted friends increases the probability of the user to convert herself. Here differences between friends from the same or from different countries are more pronounced for point-and-shoot than for digital single-lens reflex users. Fourth, there was again a distinct difference between arbitrary friends and high cliqueness friends in terms of prediction quality for conversion.

Brand Promotion Through Internet Advertising

Advertising is an important and conventional 360 degree communication used to create brand awareness. This leads to brand trial in order to convert them into raising a certain level of awareness and help them to convert into brand loyal customer, and ultimately contributing to revenue and profit generation. Internet advertising has gained immense importance and is now a crucial platform in brand development, brand promotion and brand management. With digital promotions through networking sites, anyone can get real-time results and see if their target audience are buying, watching, or downloading whatever product or service in response to social network advertising. Advertising is being done through websites, social networking sites like twitter, face book, etc. to reach out to consumers who are now heavily dependent on technology and internet. This study envisages a strong positive two way interactive correlation between internet advertising and its positive effect it has on a brand in terms of promotion and position.

Friends, Fans, and Followers: Do Ads Work on Social Networks?

ABSTRACT Social-networking sites (SNS) such as Facebook and Twitter are growing in both popularity and number of users. For advertisers and the sites themselves, it is crucial that users accept advertising as a component of the SNS. Anecdotal evidence indicates that social-networking advertising (SNA) can be effective when users accept it, but the perception of excessive commercialization may lead to user abandonment. Empirical support for these propositions, however, is lacking. Based on media uses and gratification theory, the authors propose and empirically test a model of content-related, structural, and socialization factors that affect users9 attitudes toward SNA.

THE IMPORTANCE OF DATABASE MARKETING IN SOCIAL NETWORK ADVERTISING

The last two decades have witnessed drastic globalization achievements and technological innovations that do not only have a major impact on the individual but have also produced profound changes in all aspects of business, including marketing. Owing to current trends, the means of realizing one of the primary goals of every business, that is, satisfying customers’ needs, have been greatly changed. Contemporary businesses focus their marketing efforts on creating databases of the existing customers and stimulating their company loyalty. The establishment and effective management of a customer database enables a personalized approach to every customer. It is personalization based on relevant information resulting from employing a customer database that can allow businesses to acquire new customers and retain the current ones as well as build a long-term relationship with customers that leads to greater marketing efficiency. One of the new trends that implies using databases is social networking. Social networks have thus become a location where users can not only communicate among themselves but also communicate with businesses. Without a quality database marketers would not be able to appropriately exploit social networking as an advertising medium and send personalized messages to individuals. Therefore the aim of this paper is to exemplify the importance of marketing databases in social network advertising.