Relevant bibliographies by topics / Google Analytics

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Google Analytics'

Author: Grafiati
Published: 4 June 2021
Last updated: 24 January 2023

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Journal articles on the topic "Google Analytics"

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Galbraith, Susanna. "Google Analytics." Journal of the Canadian Health Libraries Association / Journal de l'Association des bibliothèques de la santé du Canada 34, no. 2 (July 21, 2014): 119. http://dx.doi.org/10.5596/c13-022.

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McMullen, Anthony. "Google Analytics http://www.google.com/analytics/." Public Services Quarterly 6, no. 1 (February 8, 2010): 21–22. http://dx.doi.org/10.1080/15228950903517415.

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Ertel, Sebastian, and Sven Venzke-Caprarese. "Google Universal Analytics." Datenschutz und Datensicherheit - DuD 38, no. 3 (March 2014): 181–85. http://dx.doi.org/10.1007/s11623-014-0072-2.

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Reiter, Miroslav, Ondrej Čupka, and Andrej Miklošík. "Personas creation using Google Analytics." Marketing Science & Inspirations 16, no. 4 (December 30, 2021): 26–33. http://dx.doi.org/10.46286/msi.2021.16.4.4.

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This case study investigates how a marketing persona may be created with the use of data gathered by cookies and with the use of Google Analytics. The data gathered originates from the largest IT e-learning platform VITA. The basis of our research was measurement in the Google Analytics tool and the WooCommerce plug-in within the WordPress content management system. Our case study shows how a marketing persona may be created and recommends that once such a persona is created it needs to be validated repeatedly with data on real customers before it may be used for marketing purposes.
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Hansen, Marit. "Google Analytics auf dem Prüfstand." Datenschutz und Datensicherheit - DuD 32, no. 8 (August 2008): 506. http://dx.doi.org/10.1007/s11623-008-0120-x.

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Синякин, Николай. "Модели атрибуции в счетчиках Google Analytics и «Яндекс.Метрика»." Интернет-маркетинг 1 (2020): 2–14. http://dx.doi.org/10.36627/2619-1369-2020-1-1-2-14.

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Purnaningrum, Evita, and Ihdina Ariqoh2. "GOOGLE TRENDS ANALYTICS DALAM BIDANG PARIWISATA." Majalah Ekonomi 24, no. 2 (December 9, 2019): 232–43. http://dx.doi.org/10.36456/majeko.vol24.no2.a2069.

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Perkembangan era ke arah digital berakibat terdapatnya berbagai jenis data yang beragam mulai dari text, photo, video, music, postingan di sosial media dan memiliki karakteristik 4V (Volume, Velocity, Variety, Veracity) yang dikenal dengan nama Big Data. Data tersebut dapat digunakan sebagai data penelitian yang dapat meningkatkan tingkat keakurasian dalam menyelesaikan suatu permasalahan. Salah satu big data sederhana yaitu google trends yang dapat digunakan sebagai prediksi maupun kebijakan lainnya. Penelitian ini mengkaji pemanfaatan google trends dalam bidang pariwisata. Hasil dari penelitian ini adalah penelitian mengenai google trends dan pariwisata mengalami tren naik, dan sebagian besar analisis yang digunakan untuk google trends adalah prediksi. Indonesia menjadi dua puluh besar negara yang mencari istilah google trends pada mesin penulusarn web Google, namun masih jarang yang menggunakannya sebagai data penelitian, bahkan untuk pariwisata belum terdapat penelitian yang menggunakan google trends. Untuk itu, penelitian ini dapat dijadikan rujukan informasi pertama dalam pencarian google trends di bidang pariwisata.
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van Kogelenberg, Leon. "Google Analytics: wie bezoekt je site?" PodoPost 31, no. 2 (March 2018): 44–45. http://dx.doi.org/10.1007/s12480-018-0026-6.

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Plaza, Beatriz. "Google Analytics for measuring website performance." Tourism Management 32, no. 3 (June 2011): 477–81. http://dx.doi.org/10.1016/j.tourman.2010.03.015.

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Gunter, Ulrich, and Irem Önder. "Forecasting city arrivals with Google Analytics." Annals of Tourism Research 61 (November 2016): 199–212. http://dx.doi.org/10.1016/j.annals.2016.10.007.

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Dissertations / Theses on the topic "Google Analytics"

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Weida, Petr. "Využití Google Analytics v eshopu." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-85117.

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The main aim of this work is describing and explaining the possibilities of web analytics as a tool for effective evaluation of the web and campaigns performance. The benefit appreciate everybody, who makes decision on further web development and its marketing based on measured data. The work is divided into three main parts. The first describes how set up Google Analytics for measuring the web, the second part shows how read and interpret the measured data. In the third practical part are both applied for analyzing prohifi.cz shop.
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Zahradník, Jan. "Využití Google Analytics v eshopu." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-162548.

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The present thesis focuses on a specific e-shop operating mainly within the Czech market and the ways it uses one of the most significant tools of web analysis -- Google Analytics. The aim of the thesis is an analysis of the key areas, i.e. visitor analysis, visitor sourcing analysis and content analysis. The problematic areas are based on these as well as recommendations and suggestions that should help, once these have been applied, improve the service quality leading to increased revenue and better competitiveness within the market.
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Jansa, Marek. "Využití Google Analytics v e-shopu." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-124668.

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This thesis is focused on detailed description of the Web analytics tool Google Analytics and its use in improving attendance and competitiveness of Dobra vína company's e-shop. The aim is to propose measures that will increase sales of offered products. The measures were designed combining the analysis of web content, technical analysis of the web and the data obtained using Google Analytics. The thesis provides updated information on setting up Google Analytics: important changes that had taken place recently among which the transition to asynchronous syntax. These haven't been yet summarized in any other similar work. It also brings its own perspective on the use of information from Google Analytics to improve the performance of Internet business. The thesis presents the web analytics and the tool Google Analytics in general; it describes the setup and customization of the tracking code and finally it provides a short guide on how to read the visualized data. In the practical part it explores the web content of the Dobra vína's site and its technical aspects, after this it presents the specific settings of Google Analytics for the site and the final chapters analyze the data obtained from Google Analytics and propose adequate measures to take.
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Dibrova, Alisa. "Web analytics. Website analysis with Google Analytics and Yandex Metrics." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22200.

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The scope of my research is web analytics. This paper describes the process of usability analysis of the website belonging to a company Sharden Hus situated in Stockholm. From the many existing tools of web analysis I chose two the most popular ones, Google Analytics and Yandex Metrics. In similar projects that I have read, the website redesign was based on both quantitative, statistical, and qualitative (user interviews, user tests) data. In contrast to the previously carried out projects on websites improvement with the help of similar tools, I decided to base the changes on the website only on quantitative data obtained with Google and Yandex counters. This was done in order to determine whether and how Google and Yandex tools can improve the website performance. And to see if web analytics counters may provide with sufficient statistical data enough for it's correct interpretation by a web analytics designer which would lead to the improvement of the web site performance.The results of my study showed that Google and Yandex counters isolated from qualitative methods can improve the website performance. In particular, the number of visits from the territory of Sweden was increased to almost double; the overall bounce rate reduced; the number of visits to the page containing order forms significantly increased.
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Dage, Sandra. "Att hitta användbarhetsproblem med Google Analytics - är det möjligt?" Thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-306925.

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The scope of research is usability problems and web analytics. This thesis examines whether or nor Google Analytics can point out the usability problems a website has, and describes the process of usability analysis of the two websites belonging to the organisation ArtDatabanken. The research is divided into two parts. The first part describes the collection of the usability problems ArtDatabanken had and what usability problems that were identified. The second part describes the Google Analytics analysis of the usability problems that were possible to investigate, how the study was designed and the result from that investigation. Finally, some recommendations are given on how Google Analytics should be improved to more effectively find potential usability problems. The results of the research show that Google Analytics can find some of the identified usability problems, but the automatic implementation and its standard reports is not effective enough. By tracking all of the events at the site, a better understanding of what users are doing during their visits could be obtained. This together with some changes of the built-in reports would increase the possibilities to find potential usability problems by using Google Analytics.
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Hejl, Radomír. "Analytika obsahových webů." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124785.

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The thesis deals with web analytics of content based websites. Its primary aim is to design metrics of a web analysis and range of the metrics. This allows a proprietor of the content based websites to evaluate the state of the web and also its changes. The following is a practical example of handling website metrics and how to evaluate a web redesign with the help of these metrics. The first and second chapter lists literature of web analysis and specifies a purpose of the thesis and its target group. In the paragraphs that follow, I explain the theoretical starting-points and major concepts in further detail. In the third chapter I describe the main targets of content based websites because con-sequently defined metrics should reflect these targets and aim for them. Then I underline some specific problems of content based websites analysis. The fifth chapter forms the crux of this work. First, I define right metrics and then present the very design of metrics for analysis of content based websites. The proposed metrics describe interpretation of values, possibilities of segmentation and also relation to other metrics. In the fifth chapter there is an example of some metrics applied to real data of two content based websites with a description of how to work with these metrics.
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Dinis, Maria Gorete Ferreira. "Indicadores do comportamento online e tendências da procura turística: as ferramentas Google Trends e Google Analytics." Doctoral thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/16370.

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Doutoramento emTurismo
O presente trabalho de investigação tem como objetivo mostrar a capacidade das ferramentas Google Trends e Google Analytics para fornecerem indicadores, quase em tempo real, sobre os interesses e comportamentos online coletivos, com base nas pesquisas realizadas no Google e nos movimentos dos visitantes nos sites, respetivamente. Para tal, iniciou-se a investigação com uma revisão da literatura e análise de dados secundários que permitiu: conhecer as políticas, indicadores e estatísticas oficiais do turismo, a utilização da Internet e as potencialidades da web analytics, principalmente do Google Trends e Google Analytics para os agentes do turismo, bem como as determinantes, modelos e tendências da procura turística. O estudo empírico centrou-se na análise dos dados primários obtidos com as ferramentas e na relação dos dados online com os dados oficiais publicados sobre o turismo, focando-se a análise no território nacional e regiões. Os resultados obtidos mostram que o padrão de comportamento e interesses dos indivíduos que pesquisam no Google a partir do território nacional sobre os subsetores do turismo, recursos e destinos turísticos é muito similar ao verificado na realidade, e do cruzamento dos dados das pesquisas online sobre alojamento com as dormidas nos estabelecimentos hoteleiros em Portugal constatou-se que existe uma forte correlação entre os dados, com um desfasamento temporal que varia com o local de acesso à Internet do individuo. Além disso, demonstrou-se a capacidade dos dados do Google Trends como indicador avançado da procura turística em Portugal, e desenvolveram-se novos indicadores para medir o interesse online interno e externo pelo turismo em Portugal e suas regiões. Adicionalmente, foram analisados os dados obtidos através da ferramenta Google Analytics referentes ao site do turismo do Alentejo (www.visitalentejo.pt), demonstrando-se que estes fornecem informação útil para compreender o comportamento e perfil do visitante ao nível de um destino turístico regional. A tese contribuiu para mostrar o potencial da Internet como fonte de dados, e a possibilidade de utilização desses dados para obter conhecimento na área do turismo e prever com melhor precisão a procura turística de Portugal, antes da publicação oficial da informação estatística sobre o setor.
This PhD thesis aims to show the Google Trends and Google Analytics tools capabilities in providing near real time indicators for the collective online behaviour and interests, based on searches performed on the Google search engine and the movements of visitors on websites, respectively. To this end, we began the research with a literature survey and secondary data analysis, which allowed understanding the policies, the indicators, the official tourism statistics, and the utilisation in general of the Internet. Moreover, the potential of web analytics tools, namely Google Trends and Google Analytics for tourism agents, as well as the determinants, models and trends in tourism demand, were analysed. The empirical study was carried out based on the analysis of primary data obtained with the web analytics tools and the relationship of online data with official published tourism data, focusing the analysis on the Portuguese national and regional territory. The obtained results show that the pattern of interests and behaviour of individuals searching on Google from the national territory for information about the sub sectors of tourism, resources and tourism destinations is very similar to that seen in reality. By crossing the data from online searches on accommodations with overnight stays in hotels in Portugal it was found that there is a strong correlation between the data, with a time lag that varies with the individual Internet access location. Furthermore, it was demonstrated the capability of Google Trends data as a leading indicator of tourism demand in Portugal, and developed new indicators to measure internal and external online interest concerning the Portuguese tourism demand. Additionally, data obtained from Google Analytics tool related to the Alentejo site (www.visitalentejo.pt) was analysed, demonstrating that this provides useful information for understanding the behaviour and visitor profile at the level of a regional tourist destination. The thesis contributed to demonstrate the potential of the Internet as a source of data, and the possibility of using this data to gain knowledge in the field of tourism, before the official publication of statistical information about this industry, and to predict with greater accuracy the tourism demand in Portugal.
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Carlsson, Ståbi Jenny. "Data driven marketing : How to gain relevant insights through Google Analytics." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254988.

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In this report, problems regarding the retrieving, measuring, and analysis of data when analysing marketing effects in the web analytics tool Google Analytics will be discussed. A correct setup, configuration, maintenance, campaign tracking and the understanding of the data in Google Analytics is essential to be able to achieve relevant insights. This is important since many Swedish marketing departments experience issues related to their setup of Google Analytics as well as the ongoing configuration and maintenance. A literature study has been conducted to gather information, focusing on collecting theories from researchers and experts in the field of web analytics and marketing analytics. Google Analytics data and reports from several Swedish companies have been studied to gain a deep understanding of how the tool is used for the measuring and analysis of the marketing effects. Interviews with marketing department and media bureau/agency employees have been conducted and analysed in a qualitative manner. A thematic analysis of the interviews has been done, resulting in 8 themes which are presented in the result section. The result has been analysed and discussed in relation to the theory. The interviews showed that there is a difference in knowledge and experience between the senior and junior analysts, and that there is a significant learning curve when working in Google Analytics. The junior analysts trusted the data, and did not know about campaign tracking and filters, in contrast to the senior analysts, who did not trust the data as a control mechanism, and did work with campaign tracking and filters. Furthermore, the senior analysts had more understanding of the data models in Google Analytics, such as attribution models, which are known to show different stories based on which attribution model is being used. The conclusions are four capabilities that address a need for more and better control over the setup and over the data, a wider use of campaign tracking, and wider knowledge of the data and the data models in Google Analytics, and of the business the organisation is conducting, to be able to gain relevant insights.
I den här rapporten diskuteras problemen med att insamla, mäta och analysera data vid analys av marknadseffekter i webbanalys-verktyget Google Analytics. Korrekt installation, konfiguration, underhåll, kampanjspårning och förståelsen av datan i Google Analytics är viktigt för att kunna uppnå relevanta insikter. Detta är viktigt eftersom att många svenska marknadsföringsavdelningar upplever problem i samband med installationen av Google Analytics samt den pågående konfigurationen och underhållet av data som ska mätas och analyseras. En litteraturstudie har gjorts för att samla in information, med inriktning på att samla teori från forskare och experter inom webbanalys och marknadsanalys. Google Analytics-data och rapporter från flera svenska företag har studerats för att få en djupare förståelse för hur verktyget används för att mäta och analysera marknadsföringseffekter. Intervjuer med medarbetare på marknadsavdelningar och mediebyråer har genomförts och analyserats på ett kvalitativt sätt. En tematisk analys av intervjuerna har gjorts, vilket resulterat i 8 teman som presenteras i resultatavsnittet. Resultatet har analyserats och diskuterats i förhållande till teorin. Intervjuerna visade att det finns skillnad i kunskap och erfarenhet mellan seniora och juniora analytiker, och att det finns en signifikant inlärningskurva när en arbetar i Google Analytics. De juniora analytikerna litade på datan och tillämpade inte kampanjspårning och filter i motsats till de seniora analytikerna som inte litade på datan som en kontrollmekanism, samt tillämpade kampanjspårning och filter. Vidare hade de seniora analytikerna större förståelse för datamodellerna i Google Analytics, till exempel attributionsmodeller, som är kända för att indikera olika saker baserat på vilken modell som används. Slutsatserna är fyra förmågor som relaterar till ett behov av mer och bättre kontroll över datan och installationen av Google Analytics, en bredare användning av kampajspårning, bredare kunskaper om både datan och de olika datamodellerna i Google Analytics, och verksamheten som organisationen utför för att kunna tillskansa sig relevanta insikter som är lämpliga att grunda beslut utifrån.
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Fila, Ondřej. "Sledování vývoje webu po zavedení jazykové mutace /pracovní název/." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-201690.

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The first part of this thesis, Monitoring website progress after the implementation of a language mutation, focuses on the theoretical foundations of web analytics (history of web analytics, data collection methods, basic metrics) and Internet marketing (importance of Internet marketing and its distribution, Pay Per Click advertising). An analytical tool Google Analytics is also presented in this part. The analytical and application part contains a presentation of Segway-Point company and its website. On this website the progress (sessions, bounce rate, users flow, conversions, etc.) before and after the implementation of a language mutation was monitored and the ads settings using Google AdWords was set up accordingly. The result is the evaluation of hypotheses and a list of advices and recommendations for Segway-Point company.
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Paiola, Francesco. "Tracciamento degli accessi a documenti di Google Drive." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20527/.

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Al giorno d’oggi, durante conferenze o seminari, è sempre più importante ricevere dei feedback da parte degli utenti presenti riguardo ai contenuti proposti nelle presentazioni. L’acquisizione e la successiva analisi di questi dati può essere utile infatti per migliorare e arricchire tali contenuti. Numerose presentazioni sono sempre più spesso realizzate e memorizzate utilizzando dei servizi di cloud computing, che presentano il vantaggio di consentire ad altri utenti di scaricarle ed eventualmente condividerle. Il seguente elaborato di tesi tratterà la creazione di uno script in grado di tracciare i dati degli utenti che accedono ad un documento (in particolar modo ad una presentazione) su Google Drive condivisa tramite URL. I dati di accesso degli utenti che si desiderano tracciare non costituiscono di per sé un feedback da parte degli stessi, tuttavia, se opportunamente analizzati, possono ricondurre alla rilevazione di un indice di gradimento. Per il raggiungimento del suddetto obiettivo sono stati effettuati più tentativi tramite l’utilizzo di metodologie e tecnologie diverse. Alcuni di essi hanno portato a delle soluzioni al problema in esame, ma solo una è stata reputata accettabile, poiché queste soluzioni chiedevano dei compromessi che, in certi casi, sono risultati in contrasto con i requisiti funzionali minimi definiti in partenza. Si è giunti infine ad una soluzione ritenuta accettabile, la quale, seppur non priva di compromessi, non è risultata in contrasto con tali requisiti.
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Books on the topic "Google Analytics"

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L, Ledford Jerri, ed. Google Analytics. Indianapolis, IN: Wiley Technology Pub., 2007.

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Joe, Teixeira, Tyler Mary E. 1970-, and ebrary Inc, eds. Google Analytics. 3rd ed. Indianapolis, Ind: Wiley Pub., Inc., 2010.

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Aden, Timo. Google Analytics. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.

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Aden, Timo. Google Analytics. München: Carl Hanser Verlag GmbH & Co. KG, 2010. http://dx.doi.org/10.3139/9783446424005.

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Alhlou, Feras, Shiraz Asif, and Eric Fettman. Google Analytics Breakthrough. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119266365.

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1970-, Tyler Mary E., ed. Google Analytics 2.0. Indianapolis, IN: Wiley, 2007.

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Ledford, Jerri L. Google Analytics 2.0. New York: John Wiley & Sons, Ltd., 2009.

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Kelsey, Todd. Introduction to Google Analytics. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-2829-6.

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Weber, Jonathan. Practical Google Analytics and Google Tag Manager for Developers. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0265-4.

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The ultimate guide to Google analytics. North Charleston, SC: CreateSpace Independent Publishing Platform, 2012.

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Book chapters on the topic "Google Analytics"

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Amunategui, Manuel, and Mehdi Roopaei. "Google Analytics." In Monetizing Machine Learning, 393–99. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3873-8_13.

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Abuín Vences, Natalia, and Raquel Vinader Segura. "Google Analytics." In Encyclopedia of Big Data, 514–17. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-32010-6_105.

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Vences, Natalia Abuín, and Raquel Vinader Segura. "Google Analytics." In Encyclopedia of Big Data, 1–4. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-32001-4_105-1.

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Aden, Timo. "Google Analytics." In Google Analytics, 1–15. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.001.

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Aden, Timo. "Google Analytics." In Google Analytics, 1–12. München: Carl Hanser Verlag GmbH & Co. KG, 2010. http://dx.doi.org/10.3139/9783446424005.001.

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Aden, Timo. "Anmelden." In Google Analytics, 73–116. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.005.

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Aden, Timo. "Benutzeroberfläche." In Google Analytics, 259–316. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.008.

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Aden, Timo. "Startseite." In Google Analytics, 317–70. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.009.

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Aden, Timo. "Google Analytics im Einsatz." In Google Analytics, 623–51. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.017.

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Aden, Timo. "Frequently Asked Questions." In Google Analytics, 653–65. München: Carl Hanser Verlag GmbH & Co. KG, 2012. http://dx.doi.org/10.3139/9783446432826.018.

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Conference papers on the topic "Google Analytics"

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Gaur, Loveleen, Gurinder Singh, Jeyta, and Shubhankar Kumar. "Google Analytics." In the Second International Conference. New York, New York, USA: ACM Press, 2016. http://dx.doi.org/10.1145/2905055.2905251.

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Ramadas, Meera, Ved Prakash Mishra, Stefano Corti, Shah Faisal, and Vinod Kumar Shukla. "Digital Monetization and Google Analytics." In 2021 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE). IEEE, 2021. http://dx.doi.org/10.1109/iccike51210.2021.9410749.

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Martínez-Monés, Alejandra, Christophe Reffay, Javier Hoyos Torío, and Juan A. Muñoz Cristóbal. "Learning Analytics with Google Classroom." In TEEM 2017: 5th International Conference Technological Ecosystems for Enhancing Multiculturality. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3144826.3145397.

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D'Amuri, Francesco, Francesco Billari, and Juri Marcucci. "Forecasting Births Using Google." In CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/carma2016.2016.4301.

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Qin, Han, Kit Riehle, and Haozhen Zhao. "Using google analytics to support cybersecurity forensics." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258385.

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Coates, Midge. "Using google analytics to explore ETDs use." In the 13th ACM/IEEE-CS joint conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2467696.2467770.

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Romero, Enrique, Jesús Sergio Artal-Sevil, Esmeralda Mainar, and Beatriz Rubio. "GOOGLE ANALYTICS: AN INTERESTING TOOL FOR TEACHING." In 10th International Conference on Education and New Learning Technologies. IATED, 2018. http://dx.doi.org/10.21125/edulearn.2018.2507.

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Onorante, Luca, and Gary Koop. "Macroeconomic Nowcasting Using Google Probabilities." In CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/carma2016.2016.4213.

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Filva, Daniel Amo, Maria Jose Casany Guerrero, and Marc Alier Forment. "Google analytics for time behavior measurement in Moodle." In 2014 9th Iberian Conference on Information Systems and Technologies (CISTI). IEEE, 2014. http://dx.doi.org/10.1109/cisti.2014.6877095.

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Gómez Martínez, Raúl, Camilo Prado Román, and María del Carmen De la Orden de la Cruz. "Algorithmic Trading Systems Based on Google Trends." In CARMA 2018 - 2nd International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/carma2018.2018.8295.

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Abstract:
In this paper we analyze five big data algorithmic trading systems based on artificial intelligence models that uses as predictors stats from Google Trends of dozens of financial terms. The systems were trained using monthly data from 2004 to 2017 and have been tested in a prospective way from January 2017 to February 2018. The performance of this systems shows that Google Trends is a good metric for global Investors’ Mood. Systems for Ibex and Eurostoxx are not profitable but Dow Jones, S&P 500 and Nasdaq systems has been profitable using long and short positions during the period studied. This evidence opens a new field for the investigation of trading systems based on big data instead of Chartism.
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