As part of the promotional mix, advertising plays a significant role in a company’s or organisation’s communication with its consumers and stakeholders. In order to inform consumers about their products or services, marketers apply a variety of advertising strategies. One particular strategy is “contextual advertising”, which refers to the strategic placement of advertisements in an editorial environment whose theme is relevant for the promoted product or service (Belch & Belch, 2009, p. 492). Also in advertising research, contextual advertising received a considerable amount of attention. Scholars have investigated the effectiveness of contextual advertising in online and offline media. Researchers as well as practitioners have particularly focused on content-based relationships between advertisements and the theme of the editorial environment in which the advertisement is placed. With a focus on online media, the present study aimed to investigate this content-based relationship but also to examine what other types of relationships between the different contents on a webpage the user constructs. Advertising has also been investigated in the area of semiotics. Several scholars analysed advertisements in order to reveal their meaning-affordances. A second interest in the present study derives from semiotic studies and theories, which emphasise the individual’s significance in the meaning-making process but also exclude the individual from their analysis. A potential contradiction could be seen here and by investigating how users interpret a particular webpage, this study aimed to examine what insights an analysis can provide that is solely focused on the webpage user. In order to capture users’ interpretations of a webpage’s contents and to investigate what types of relationships between these contents users construct semi-structured interviews with six participants were conducted. The participants were invited to look at a webpage from the website www.healthyfood.co.nz. Following the interviews, the participants’ responses were transcribed, categorised and analysed. Findings from the study revealed that several participants constructed relationships between advertisements and the editorial content based on content-similarity but also on design-similarity as well as their personal knowledge about sponsorship relationships and income-investment relationships. Personal knowledge also appeared to be important for the interpretation of the webpage. The participants’ interpretation of the webpage were also guided by their personal interest in the contents, their individual contexts like socio-cultural background, experiences and beliefs as well as environmental factors such as time and the layout of the interview location. The results of the study support the significant role of the individual in the process of meaning making and further contribute to an extended understanding of contextual advertising. Practical suggestions for the advertising area and future research were also identified.

As part of the promotional mix, advertising plays a significant role in a company’s or organisation’s communication with its consumers and stakeholders. In order to inform consumers about their products or services, marketers apply a variety of advertising strategies. One particular strategy is “contextual advertising”, which refers to the strategic placement of advertisements in an editorial environment whose theme is relevant for the promoted product or service (Belch & Belch, 2009, p. 492). Also in advertising research, contextual advertising received a considerable amount of attention. Scholars have investigated the effectiveness of contextual advertising in online and offline media. Researchers as well as practitioners have particularly focused on content-based relationships between advertisements and the theme of the editorial environment in which the advertisement is placed. With a focus on online media, the present study aimed to investigate this content-based relationship but also to examine what other types of relationships between the different contents on a webpage the user constructs. Advertising has also been investigated in the area of semiotics. Several scholars analysed advertisements in order to reveal their meaning-affordances. A second interest in the present study derives from semiotic studies and theories, which emphasise the individual’s significance in the meaning-making process but also exclude the individual from their analysis. A potential contradiction could be seen here and by investigating how users interpret a particular webpage, this study aimed to examine what insights an analysis can provide that is solely focused on the webpage user. In order to capture users’ interpretations of a webpage’s contents and to investigate what types of relationships between these contents users construct semi-structured interviews with six participants were conducted. The participants were invited to look at a webpage from the website www.healthyfood.co.nz. Following the interviews, the participants’ responses were transcribed, categorised and analysed. Findings from the study revealed that several participants constructed relationships between advertisements and the editorial content based on content-similarity but also on design-similarity as well as their personal knowledge about sponsorship relationships and income-investment relationships. Personal knowledge also appeared to be important for the interpretation of the webpage. The participants’ interpretation of the webpage were also guided by their personal interest in the contents, their individual contexts like socio-cultural background, experiences and beliefs as well as environmental factors such as time and the layout of the interview location. The results of the study support the significant role of the individual in the process of meaning making and further contribute to an extended understanding of contextual advertising. Practical suggestions for the advertising area and future research were also identified.

Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-06-22T14:20:17Z No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T13:07:06Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T13:07:02Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-06-24T14:44:22Z (GMT) No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) / Made available in DSpace on 2015-06-24T14:44:22Z (GMT). No. of bitstreams: 1 Tese - Klessius Renato Berlt.pdf: 972646 bytes, checksum: c127b522da4fc3719f61df80976a23ad (MD5) Previous issue date: 2012-12-19 / CNPQ - Conselho Nacional de Desenvolvimento Científico e Tecnológico / In this work we address the problem of selecting keywords for contextual advertising systems in two di erent scenarios: web pages and short texts. We deal with the problem of selecting keywords from web pages using machine learning. While traditional machine learning approaches usually have the goal of selecting keywords considered as good by humans. The new machine learning strategy proposed drives the selection by the expected impact of the keyword in the nal quality of the ad placement system, which we name here as ad collection aware keyword selection (also referred in this work as ACAKS). This new approach relies on the judgement of the users about the ads each keyword can retrieve. Although this strategy requires a higher e ort to build the training set than previous approaches, we believe the gain obtained in recall is worth enough to make the ad collection aware approach a better choice. In experiments we performed with an ad collection and considering features proposed in a previous work, we found that the new ad collection aware approach led to a gain of 62% in recall over the baseline without dropping the precision values. Besides the new alternative to select keywords, we also study the use of features extracted from the ad collection in the task of selecting keywords. We also present three new methods to extract keywords from web pages which require no learning process and use Wikipedia as an external source of information to support the keyword selection. The information used from Wikipedia includes the titles of articles, co-occurrence of keywords and categories associated with each Wikipedia de nition. Experimental results show that our methods are quite competitive solutions for the task of selecting good keywords to represent target web pages, albeit being simple, e ective and time e cient. Besides selecting keywords from web pages we also study methods for selecting keywords from short texts. Short texts have became a very popular way users adopt for publishing content on the web. Every day, millions of users post their thoughts, needs and feelings on the Web through systems, such as social networks like Facebook and Twitter, or spaces for comments on news web sites. Much of these systems' revenue is from contextual advertising systems, thus selecting keywords in this new scenario raise as a new challenge. We propose and study a novel family of methods which uses the connectivity information present on Wikipedia to discover the most related concepts on each short textual unit. We also used the proposed methods as a new set of features on a Machine Learning Framework to boost the quality of the results obtained. We show that this approach presents a good performance and outperforms the best baselines by more than 35%. Finally, we apply the ACAKS approach on short texts and it yielded good results, outperforming a traditional machine learning approach by more than 80% in precision and 80% in recall. / Neste trabalho, nós estudamos o problema de seleção de palavras-chave para sistemas de publicidade contextualizada em dois diferentes cenários: páginas web e textos curtos. Nós lidamos com o problema de seleção de palavras-chave em páginas web utilizando aprendizado de máquina. Abordagens tradicionais baseadas em aprendizado de máquina geralmente possuem como objetivo selecionar palavras-chave consideradas como relevantes por um conjunto de usuários. Entretanto, a nova estratégia proposta nesse trabalho objetiva selecionar palavras-chave que gerem o melhor resultado na qualidade final do sistema de seleção de publicidade. A esta estratégia, nós demos o nome de ad collection aware keyword selection (também chamada de ACAKS). Esta nova abordagem baseia-se no julgamento dos usuário em relação às propagandas com as quais cada palavra-chave _e relacionada pelo sistema de seleção de publicidade. Apesar desta estratégia demandar um alto esforço para rotular o conjunto de treino em relação _as abordagens tradicionais, nós acreditamos que o ganho obtido em revocação é suficiente para fazer com que o ACAKS seja uma melhor alternativa. Nos experimentos que nós realizamos com uma coleção de anúncios e considerando as características propostas em um trabalho anterior, nós descobrimos que a nova abordagem proposta levou a um ganho de 62% em revocação em relação ao baseline utilizado sem perder precisão. Além desta nova alternativa para selecionar palavras-chave, nós estudamos ainda a utilização do conjunto de características estraída da coleção de anúncios para selecionar palavras-chave. Nós também apresentamos três novos métodos para extrair palavras chave de páginas web que não necessitam de treino e usam a Wikipédia como fonte externa de informação. A informação usada da Wikipédia inclui os títulos dos artigos, co ocorrência de palavras chave e categorias associadas com cada artigo da Wikipédia. Resultados experimentais mostram que nossos métodos são soluções competitivas para selecionar boas palavras-chave que representem bem o conteúdo de páginas web, enquanto se mantém simples eficientes. Além da seleção de palavras-chave de paginas web nós também estudamos métodos para selecionar palavras-chave em textos curtos. Textos curtos tem se tornado uma maneira muito popular que os usuários encontraram para publicar conteúdo na web. Todos os dias, milhões de usuários postam seus pensamentos, necessidades e sentimentos na web através de sistemas de redes sociais, como Facebook e Twitter, ou espaços para comentários em sites de notícias. Grande parte da renda destes sistemas _e proveniente de publicidade contextualizada, desta forma selecionar palavras-chave neste novo cenário surge como um novo desafio. Nós propomos e estudamos uma nova família de métodos que utiliza a informação de conectividade presente na Wikipédia para descobrir os conceitos mais relacionados em cada texto curto. Utilizamos também os métodos propostos como um novo conjunto de características em um Framework de aprendizado de máquina para melhorar a qualidade dos resultados obtidos. Nós mostramos que esta abordagem apresenta um bom desempenho e supera o melhor baseline em cerca de 35%. Finalmente, nós aplicamos a abordagem ACAKS em textos curtos e ele gerou bons resultados, superando uma abordagem tradicional baseada em aprendizado de máquina em cerca de 80% tanto em termos de precisão quanto revocação.

This diploma work deals with specific business concept and with possibilities of a company promotion on the Internet. The theoretical segment contains a survey of the Internet business models and a synopsis of current individual forms of promotion used on the Internet. There are described advantages and disadvantages of banner advertising, contextual advertising, email marketing, search engine marketing (SEM), social networks and affiliate marketing. The final part of theoretical section of the thesis is dedicated to the possibilities of propagation efficiency measurements. Practical part of the diploma work introduces author's own business concept and its business model. The description of specific methods of propagation realized in congruence with the noted business concept follows.

The diploma thesis deals with contextual advertising with a view to Google AdWords. The aim of the thesis is to build a Google AdWords account for a non-profit organization TJ Sokol and to evaluate successfulness as well as potential of these form of advertising in non-profit organizations. In theoretical framework there is a definition of contextual advertising, briefly described its history, principle, advantages and disadvantages. Furthermore there are various contextual advertising systems in Czech Republic compared to each other. The thesis focuses in detail on Google AdWords system description from the initial account creation to its basic parts -- campaigns, ad groups, keywords, ads and conversions. This part also deals with the connection to web analytical service Google Analytics. The account creation for non-profit organization TJ Sokol is described in practical section of the thesis. The preparations which needed to be done, account development and account optimization are mentioned in this section as well. Final Google AdWords performance evaluation is generalized to small non-profit organizations and general recommendations for effective and successful ad campaigns are made based on this evaluation.

This work deals with internet advertising. Describes the basic characteristics of Internet marketing, survey errors that nascent entrepreneurs engage in formulating goals. Discusses the different types of advertising on the Internet usable in terms of functionality, payment options. It also offers an overview of advertising systems that provide these types of ads. In connection with advertising, the work deals with the problem of blocking. On show are the best known systems that block ads, but also ways to bypass such systems. The aim is to give people who want to invest money into advertising, relevant information about our services and help them choose the right type of promotion for your website. According to predefined criteria to verify the suitability of advertising and advertising system on the guesthouse accommodation in Spindleruv Mlyn. The performance is selected advertising system, its functions, a detailed procedure for creating the campaign and its optimization. The results presented show that the ad was chosen correctly. In addition, there are suggested ways to improve an existing campaign.

Otimizar simultaneamente os interesses dos usuários, anunciantes e publicadores é um grande desafio na área de publicidade computacional. Mais precisamente, a ordenação de anúncios, ou ad ranking, desempenha um papel central nesse desafio. Por outro lado, nem mesmo as melhores fórmulas ou algoritmos de ordenação são capazes de manter seu status por um longo tempo em um ambiente que está em constante mudança. Neste trabalho, apresentamos uma análise orientada a dados que mostra a importância de combinar diferentes dimensões de publicidade computacional por meio de uma abordagem evolutiva para ordenação de anúncios afim de responder a mudanças de forma mais eficaz. Nós avaliamos as dimensões de valor comercial, desempenho histórico de cliques, interesses dos usuários e a similaridade textual entre o anúncio e a página. Nessa avaliação, nós averiguamos o desempenho e a correlação das diferentes dimensões. Como consequência, nós desenvolvemos uma abordagem evolucionária para combinar essas dimensões. Essa abordagem é composta por três partes: um repositório de configurações para facilitar a implantação e avaliação de experimentos de ordenação; um componente evolucionário de avaliação orientado a dados; e um motor de programação genética para evoluir fórmulas de ordenação de anúncios. Nossa abordagem foi implementada com sucesso em um sistema real de publicidade computacional responsável por processar mais de quatorze bilhões de requisições de anúncio por mês. De acordo com nossos resultados, essas dimensões se complementam e nenhuma delas deve ser neglicenciada. Além disso, nós mostramos que a combinação evolucionária dessas dimensões não só é capaz de superar cada uma individualmente, como também conseguiu alcançar melhores resultados do que métodos estáticos de ordenação de anúncios. / Simultaneous optimization of users, advertisers and publishers\' interests has been a formidable challenge in online advertising. More concretely, ranking of advertising, or more simply ad ranking, has a central role in this challenge. However, even the best ranking formula or algorithm cannot withstand the ever-changing environment of online advertising for a long time. In this work, we present a data-driven analysis that shows the importance of combining different aspects of online advertising through an evolutionary approach for ad ranking in order to effectively respond to changes. We evaluated aspects ranging from bid values and previous click performance to user behavior and interests, including the textual similarity between ad and page. In this evaluation, we assessed commercial performance along with the correlation between different aspects. Therefore, we proposed an evolutionary approach for combining these aspects. This approach was composed of three parts: a configuration repository to facilitate deployment and evaluation of ranking experiments; an evolutionary data-based evaluation component; and a genetic programming engine to evolve ad ranking formulae. Our approach was successfully implemented in a real online advertising system that processes more than fourteen billion ad requests per month. According to our results, these aspects complement each other and none of them should be neglected. Moreover, we showed that the evolutionary combination of these aspects not only outperformed each of them individually, but was also able to achieve better overall results than static ad ranking methods.

Otimizar simultaneamente os interesses dos usuários, anunciantes e publicadores é um grande desafio na área de publicidade computacional. Mais precisamente, a ordenação de anúncios, ou ad ranking, desempenha um papel central nesse desafio. Por outro lado, nem mesmo as melhores fórmulas ou algoritmos de ordenação são capazes de manter seu status por um longo tempo em um ambiente que está em constante mudança. Neste trabalho, apresentamos uma análise orientada a dados que mostra a importância de combinar diferentes dimensões de publicidade computacional por meio de uma abordagem evolutiva para ordenação de anúncios afim de responder a mudanças de forma mais eficaz. Nós avaliamos as dimensões de valor comercial, desempenho histórico de cliques, interesses dos usuários e a similaridade textual entre o anúncio e a página. Nessa avaliação, nós averiguamos o desempenho e a correlação das diferentes dimensões. Como consequência, nós desenvolvemos uma abordagem evolucionária para combinar essas dimensões. Essa abordagem é composta por três partes: um repositório de configurações para facilitar a implantação e avaliação de experimentos de ordenação; um componente evolucionário de avaliação orientado a dados; e um motor de programação genética para evoluir fórmulas de ordenação de anúncios. Nossa abordagem foi implementada com sucesso em um sistema real de publicidade computacional responsável por processar mais de quatorze bilhões de requisições de anúncio por mês. De acordo com nossos resultados, essas dimensões se complementam e nenhuma delas deve ser neglicenciada. Além disso, nós mostramos que a combinação evolucionária dessas dimensões não só é capaz de superar cada uma individualmente, como também conseguiu alcançar melhores resultados do que métodos estáticos de ordenação de anúncios. / Simultaneous optimization of users, advertisers and publishers\' interests has been a formidable challenge in online advertising. More concretely, ranking of advertising, or more simply ad ranking, has a central role in this challenge. However, even the best ranking formula or algorithm cannot withstand the ever-changing environment of online advertising for a long time. In this work, we present a data-driven analysis that shows the importance of combining different aspects of online advertising through an evolutionary approach for ad ranking in order to effectively respond to changes. We evaluated aspects ranging from bid values and previous click performance to user behavior and interests, including the textual similarity between ad and page. In this evaluation, we assessed commercial performance along with the correlation between different aspects. Therefore, we proposed an evolutionary approach for combining these aspects. This approach was composed of three parts: a configuration repository to facilitate deployment and evaluation of ranking experiments; an evolutionary data-based evaluation component; and a genetic programming engine to evolve ad ranking formulae. Our approach was successfully implemented in a real online advertising system that processes more than fourteen billion ad requests per month. According to our results, these aspects complement each other and none of them should be neglected. Moreover, we showed that the evolutionary combination of these aspects not only outperformed each of them individually, but was also able to achieve better overall results than static ad ranking methods.

Диссертация посвящена вопросам социального маркетинга – Social Media Marketing (SMM). Рассматривается статистика продвижения товаров и услуг через работу в социальных сетях. Предметом анализа выступает инструментарий SMM, статистика активных пользователей и капитализация компаний. Результаты исследования могут быть применены в сфере организации SMM-продвижения бизнес-процессов и подготовки студентов в области онлайн-маркетинга. / The article is devoted to the issues of network marketing – Social Media Marketing (SMM). We Сonsider the statistics of the promotion of goods and services through the work in social networks. The subject of the analysis is the SMM toolkit and its system application. The results of the study can be applied in the organization of SMM-support business processes and prepare students in the field of online marketing.