scholarly journals WEB SCRAPING E CIÊNCIA DE DADOS NA PESQUISA APLICADA EM COMUNICAÇÃO: um estudo sobre avaliações online

2021 ◽  
Vol 7 (3) ◽  
pp. a1pt
Author(s):  
Marcello Tenorio de Farias ◽  
Alan César Belo Angeluci ◽  
Brasilina Passarelli
Keyword(s):  
Google Maps ◽  
Web Scraping

O web scraping se apresenta hoje como técnica valiosa para a obtenção de insights de grandes bases de dados como as decorrentes, por exemplo, da interação de usuários com a web e redes sociais, cujas informações seriam de difícil coleta e análise por meio de métodos manuais. Neste estudo aplicado, demonstrou-se a contribuição do desenvolvimento e uso de um protótipo de ferramenta para raspagem de dados de avaliações online feitas no Google Maps. O objetivo foi investigar como essas avaliações podem influenciar comportamentos dos usuários da plataforma. Dentre os resultados, observou-se que a leitura e postagem de avaliações suscitou nos usuários do Google Maps investigados reflexões sobre formação de opinião, motivações e senso crítico.

scholarly journals WEB SCRAPING AND DATA SCIENCE IN APPLIED RESEARCH IN COMMUNICATION: a study on online reviews

2021 ◽  
Vol 7 (3) ◽  
pp. a1en
Author(s):  
Marcello Tenorio de Farias ◽  
Alan César Belo Angeluci ◽  
Brasilina Passarelli
Keyword(s):  
Data Science ◽  
Applied Research ◽  
Online Reviews ◽  
Google Maps ◽  
Automatic Data ◽  
Applied Study ◽  
Prototype Tool ◽  
Web Scraping ◽  
Manual Methods ◽  
The Web

With the spread of access and use of information through the web and social networks, information retrieval in large volumes of data has become unfeasible by manual methods. In this applied study, the contribution of the development and use of a prototype tool for automatic data scraping from online evaluations made on Google Maps – Discovery Stars – was reported. The retrieved data allowed us to investigate how these assessments can have the potential to influence the behavior of the platform's users. Among the results, it was observed that the reading and posting of reviews impact the formation of opinion and motivations of Google Maps users.  

scholarly journals KAJIAN PEMANFAATAN DATA GOOGLE MAPS DALAM OFFICIAL STATISTICS

2021 ◽  
Vol 2020 (1) ◽  
pp. 328-337
Author(s):  
Cholifa Fitri Annisa ◽  
Setia Pramana
Keyword(s):  
Official Statistics ◽  
Data Frame ◽  
Google Maps ◽  
Web Scraping

Publikasi statistik usaha penyediaan makan minum yang diterbitkan oleh BPS tidak bisa memfasilitasi pebisnis dalam mengidentifikasikan daerah yang berpotensi memiliki kemampuan untuk dikembangkan usaha pada sektor penyediaan makan dan minum. Selain itu, adanya keterbatasan waktu, biaya, dan tenaga dalam pengumpulan data oleh Subdirektorat Pariwisata BPS pada survei VREST sehingga, menyebabkan statistik penyediaan makan minum tidak bisa di terbitkan sesuai metodologi yaitu setiap tahun. Penelitian ini memanfaatkan metode web scraping untuk mendapatkan data usaha penyedia makan minum dari situs web google maps. Jumlah data yang terkumpul sebanyak 34.526 usaha penyedia makan minum di Pulau Jawa dan Bali. Hasil nilai pencocokan data hasil web scraping dengan data frame BPS menunjukkan persentase kemiripan (match) sebesar 68,22%. Provinsi Bali adalah daerah yang memiliki potensi untuk mengembangkan usaha penyediaan makanan minuman terkhusus pada Kota/Kabupaten Jembrana, Buleleng, Tabanan, Karangasem, dan Klungkung. Sedangkan, provinsi Jawa Tengah adalah daerah yang memiliki potensi untuk mengembangkan usaha akomodasi terkhusus pada Kota/Kabupaten Cilacap, Blora, Grobogan, Batang, dan Kendal.

Web scraping e diritti di proprietà intellettuale nell'intermediazione di biglietti aerei low cost

2018 ◽  
pp. 120-164
Author(s):  
Alessandra Corigliano
Keyword(s):  
Low Cost ◽  
Web Scraping

Nella sentenza di seguito commentata, la Corte d'Appello di Milano, in merito alla decisione di Ryanair di escludere qualsiasi intermediazione commerciale nella vendita dei propri biglietti aerei, si è pronunciata nella vertenza tra la compagnia aerea irlandese e l'agenzia di viaggi italiana Viaggiare che, in primo grado, ha denunciato il comportamento di Ryanair in quanto avrebbe ostacolato con il proprio comportamento l'agenzia di viaggio nella vendita dei biglietti aerei di Ryanair direttamente ai consumatori, costringendo l'agenzia stessa a riutilizzare i dati forniti dal database di Ryanair al fine di vendere indirettamente i biglietti sul suo sito web. La Corte (in parziale riforma della sentenza del Tribunale di primo grado) ha ritenuto che la decisione della compagnia aerea di riservarsi la vendita di biglietti aerei non costituisse un abuso di posizione dominante come previsto dall'articolo 102 del Trattato sul Funzionamento dell'Unione Europea, in quanto Ryanair deteneva nel mercato dei voli europei solo il 10%, quota questa molto bassa, che varrebbe a escludere una posizione dominante della compagnia su detto mercato. Nell'ottica della normativa antitrust, è stata accolta la mozione di Ryanair volta ad escludere una posizione dominante sul mercato dei voli europei, mentre nell'ottica dei diritti di proprietà intellettuale la domanda di Ryanair è stata respinta. A questo proposito, la Corte non ha accolto la mozione di Ryanair in base alla quale l'uso dei suoi marchi da parte di Viaggiare violasse i diritti privativi di Ryanair; la Corte ha inoltre stabilito che il database di Ryanair non potesse essere considerato di proprietà di quest'ultima, in quanto lo stesso, essendo del tutto svincolato da specifiche tecniche e funzionali che ne dettano la scelta e l'organizzazione dei dati, non può essere considerato alla stregua di una manifestazione creativa e, quindi, proprietà intellettuale ai sensi dell'art. 2, 64-quinques e 64-sexies della Legge sul Copyright. La Corte ha quindi ritenuto che non vi fosse nemmeno protezione ai sensi della cosiddetta dottrina "sui generis" del database Rynair poiché la protezione di tale database era finalizzata ad escludere la commercializzazione dei biglietti aerei e non a proteggere gli sforzi di investimento di Ryanair. La condotta di Viagiare di "screen scraping" dei dati Ryanair relativi all'offerta di biglietti aerei è stata considerata legittima in quanto Ryanair - nei Termini di Utilizzo del suo sito web - ha fornito l'accesso (concessione di licenza) a terzi dei suoi dati

PERANCANGAN APLIKASI LOKASI TAMBAL BAN DI PONOROGO BERBASIS ANDROID

KOMPUTEK ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Irfan Khoirul Arifin ◽  
Aliyadi Aliyadi ◽  
Yovi Litanianda
Keyword(s):  
Location Based Service ◽  
Surrounding Area ◽  
Repair Shop ◽  
Google Maps ◽  
Information Media ◽  
Service Location

The number of vehicles in Indonesia continues to increase every year. This also happened in Ponorogo regency. It will also be directly proportional to the number of people who have problems with their vehicles, such as leaked tire quotes for being nailed or other causes. And will also increase the need for tire services. For motorists who are less aware of the surrounding area when experiencing damage to motorcycle tires, then of course to find a place nearest tire patch will be quite difficult. Therefore in this study developed information media for Android-based applications to map the locations - tire patch locations in Ponorogo, as well as looking for the closest tire patch with the rider. This app is a location-based service (location-based service) to the driver with the nearest patch of the banal location. Based on the results of testing this application can help users find the location of location preservation, tar bambal patch location, tire repair shop list, and tire repair shop list distance. This application can also show each other the location in accordance with the location of google maps applications. 

The impact of Airbnb on a non-touristic city. A Case study of short-term rentals in Santa Cruz de Tenerife (Spain)

Erdkunde ◽  
2020 ◽  
Vol 74 (3) ◽  
pp. 191-204
Author(s):  
Marcus Hübscher ◽  
Juana Schulze ◽  
Felix zur Lage ◽  
Johannes Ringel
Keyword(s):  
Santa Cruz ◽  
Short Term ◽  
Rental Market ◽  
Rural Space ◽  
Use Of Data ◽  
Web Scraping ◽  
Per Capita ◽  
Per Se ◽  
The Impact

Short-term rentals such as Airbnb have become a persistent element of today’s urbanism around the globe. The impacts are manifold and differ depending on the context. In cities with a traditionally smaller accommodation market, the impacts might be particularly strong, as Airbnb contributes to ongoing touristification processes. Despite that, small and medium-sized cities have not been in the centre of research so far. This paper focuses on Santa Cruz de Tenerife as a medium-sized Spanish city. Although embedded in the touristic region of the Canary Islands, Santa Cruz is not a tourist city per se but still relies on touristification strategies. This paper aims to expand the knowledge of Airbnb’s spatial patterns in this type of city. The use of data collected from web scraping and geographic information systems (GIS) demonstrates that Airbnb has opened up new tourism markets outside of the centrally established tourist accommodations. It also shows that the price gap between Airbnb and the housing rental market is broadest in neighbourhoods that had not experienced tourism before Airbnb entered the market. In the centre the highest prices and the smallest units are identified, but two peripheral quarters stand out. Anaga Mountains, a natural and rural space, has the highest numbers of Airbnb listings per capita. Suroeste, a suburban quarter, shows the highest growth rates on the rental market, which implies a linkage between Airbnb and suburbanization processes.

scholarly journals Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance

2021 ◽  
Vol 13 (11) ◽  
pp. 5839
Author(s):  
Siriwan Kajornkasirat ◽  
Jareeporn Ruangsri ◽  
Charuwan Sumat ◽  
Pete Intaramontri
Keyword(s):  
Water Quality ◽  
Growth Performance ◽  
Mobile Application ◽  
Database Management System ◽  
Quality Data ◽  
Analysis Tool ◽  
Quality Factors ◽  
Google Maps ◽  
Water Quality Data ◽  
Shrimp Farm

An online analytic service system was designed as a web and a mobile application for shrimp farmers and shrimp farm managers to manage the growth performance of shrimp. The MySQL database management system was used to manage the shrimp data. The Apache Web Server was used for contacting the shrimp database, and the web content displays were implemented with PHP script, JavaScript, and HTML5. Additionally, the program was linked with Google Charts to display data in various graphs, such as bar graphs and scatter diagrams, and Google Maps API was used to display water quality factors that are related to shrimp growth as spatial data. To test the system, field survey data from a shrimp farm in southern Thailand were used. Growth performance of shrimp and water quality data were collected from 13 earthen ponds in southern peninsular Thailand, located in the Surat Thani, Krabi, Phuket, and Satun provinces. The results show that the system allowed administrators to manage shrimp and farm data from the field sites. Both mobile and web applications were accessed by the users to manage the water quality factors and shrimp data. The system also provided the data analysis tool required to select a parameter from a list box and shows the association between water quality factors and shrimp data with a scatter diagram. Furthermore, the system generated a report of shrimp growth for the different farms with a line graph overlay on Google Maps™ in the data entry suite via mobile application. Online analytics for the growth performance of shrimp as provided by this system could be useful as decision support tools for effective shrimp farming.

Color Trend Analysis using Machine Learning with Fashion Collection Images

2021 ◽  
pp. 0887302X2199594
Author(s):  
Ahyoung Han ◽  
Jihoon Kim ◽  
Jaehong Ahn
Keyword(s):  
Machine Learning ◽  
Trend Analysis ◽  
Image Data ◽  
Fashion Industry ◽  
Color Palette ◽  
Web Scraping ◽  
Design Variables ◽  
Sales Organizations ◽  
Fashion Designers ◽  
Selection Of

Fashion color trends are an essential marketing element that directly affect brand sales. Organizations such as Pantone have global authority over professional color standards by annually forecasting color palettes. However, the question remains whether fashion designers apply these colors in fashion shows that guide seasonal fashion trends. This study analyzed image data from fashion collections through machine learning to obtain measurable results by web-scraping catwalk images, separating body and clothing elements via machine learning, defining a selection of color chips using k-means algorithms, and analyzing the similarity between the Pantone color palette (16 colors) and the analysis color chips. The gap between the Pantone trends and the colors used in fashion collections were quantitatively analyzed and found to be significant. This study indicates the potential of machine learning within the fashion industry to guide production and suggests further research expand on other design variables.

scholarly journals “In cities, it’s not far, but it takes long”: comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria

2021 ◽  
Vol 6 (1) ◽  
pp. e004318
Author(s):  
Aduragbemi Banke-Thomas ◽  
Kerry L M Wong ◽  
Francis Ifeanyi Ayomoh ◽  
Rokibat Olabisi Giwa-Ayedun ◽  
Lenka Benova
Keyword(s):  
Travel Time ◽  
Friction Surface ◽  
Obstetric Care ◽  
Travel Times ◽  
Night Time ◽  
Google Maps ◽  
Surface Approach ◽  
Low Resource ◽  
Life Saving ◽  
The Cost

BackgroundTravel time to comprehensive emergency obstetric care (CEmOC) facilities in low-resource settings is commonly estimated using modelling approaches. Our objective was to derive and compare estimates of travel time to reach CEmOC in an African megacity using models and web-based platforms against actual replication of travel.MethodsWe extracted data from patient files of all 732 pregnant women who presented in emergency in the four publicly owned tertiary CEmOC facilities in Lagos, Nigeria, between August 2018 and August 2019. For a systematically selected subsample of 385, we estimated travel time from their homes to the facility using the cost-friction surface approach, Open Source Routing Machine (OSRM) and Google Maps, and compared them to travel time by two independent drivers replicating women’s journeys. We estimated the percentage of women who reached the facilities within 60 and 120 min.ResultsThe median travel time for 385 women from the cost-friction surface approach, OSRM and Google Maps was 5, 11 and 40 min, respectively. The median actual drive time was 50–52 min. The mean errors were >45 min for the cost-friction surface approach and OSRM, and 14 min for Google Maps. The smallest differences between replicated and estimated travel times were seen for night-time journeys at weekends; largest errors were found for night-time journeys at weekdays and journeys above 120 min. Modelled estimates indicated that all participants were within 60 min of the destination CEmOC facility, yet journey replication showed that only 57% were, and 92% were within 120 min.ConclusionsExisting modelling methods underestimate actual travel time in low-resource megacities. Significant gaps in geographical access to life-saving health services like CEmOC must be urgently addressed, including in urban areas. Leveraging tools that generate ‘closer-to-reality’ estimates will be vital for service planning if universal health coverage targets are to be realised by 2030.

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