bluuebunny/crossref_metadata_2025 huggingface dataset:
ABSOLUTE COREGISTRATION AND DOMING CORRECTION IN ADVERSE CONDITIONS, OR HOW TO RETRIEVE SNOW DEPTH FROM DRONE FLIGHTS
Authors: Girod L. , Filhol S.
Published: August 2020

Abstract. Doming, a superimposition of a scene-wide dome-shaped bias to the elevation data, is a classical problem in photogrammetry, especially when using the auto-calibration and bundle adjustment typical of the Structure-from-Motion approach. A number of solutions have been proposed, but most rely on a certain degree of freedom in the data acquisition strategy, such as the ability to acquire many ground control points or to acquire additional imagery over the area of interest with different flight parameters.In this paper, we present a method to solve for the dome when working on a snowfield in the Norwegian mountains. That specific situation leads to difficulties to fly the drone optimally and acquire ground control points due to short weather windows, high winds, cold temperatures, low sun angles and short day duration (i.e. high latitudes). Here, we use natural landmarks and pre-existing knowledge about the bare ground topography for removing the inevitable dome.
EARTHQUAKE-DAMAGED REGIONS DETECTION FROM HIGH RESOLUTION IMAGE BASED ON SUPER-PIXEL SEGMENTATION AND DEEP LEARNING
Authors: Liu C. , Sui H. , Peng Y. , Hua L. , Li Q.
Published: August 2020

Abstract. Accurate detection and automatic processing of earthquake-damaged regions is essential for effective rescue and post-disaster reconstruction. In this study, we proposed a Combined Super-pixel Segmentation and AlexNet Detection approach (CSSAD) for automatically extracting damaged regions from post-earthquake high-resolution images. Simple Linear Iterative Clustering (SLIC) algorithm was used to segment the high resolution images to obtain more homogeneous geo-objects. Multiscale samples database, which took the different scale effect of damaged regions into account, was constructed based on the geometric centre of each super-pixel. AlexNet, which achieved the automatic extraction of high-level features and accurate identification of target geo-objects, was used to detect the damaged regions. To enhance the localization accuracy, the output of AlexNet was further refined using super-pixel segmentations and masked out of shadow and vegetation. Compared with traditional method, the proposed approach effectively reduces the false and missed detection ratio at least 10 percent.
OBJECT BASED IMAGE ANALYSIS AND TEXTURE FEATURES FOR PASTURE CLASSIFICATION IN BRAZILIAN SAVANNAH
Authors: Girolamo-Neto C. D. , Sato L. Y. , Sanches I. D. , Silva I. C. O. , Rocha J. C. S. , Almeida C. A.
Published: August 2020

Abstract. The classification of different types of pasture using remote sensing imagery is still a challenge. Assessing high quality geospatial information of pasture management system and productivity are key factors for establishing local public policies related to food security. In this context, we aim to investigate how texture features, allied with Object Based Image Analysis, can contribute to the automatic classification of herbaceous pastures and shrubby pastures in a region of Brazilian Savannah. We used Sentinel-2 images from dry and rainy seasons to extract several vegetation indexes, spectral unmixing components and texture features. The SLIC algorithm was used for perform image segmentation and the Random Forest for image classification. The use of texture features on pasture classification resulted in an accuracy of 87.03%. Our key finding is that features like entropy and contrast were able to detect areas with a greater concentration of shrubby-arboreal elements, which are often present on shrubby pastures and may be the first signal of a degradation process.
ACCURATE MAPPING OF DATE PALMS AT DIFFERENT AGE-STAGES FOR THE PURPOSE OF ESTIMATING THEIR BIOMASS
Authors: Issa S. M. , Dahy B. S. , Saleous N.
Published: August 2020

Abstract. The main objective of the current study was to produce an accurate map of date palm (DP) plantations in the Emirate of Abu Dhabi in United Arab Emirates (UAE) using moderate resolution Landsat-8 (OLI) imagery. The second objective was to be able to create a more detailed map depicting three different categories of date palms at three different age stages: young, medium, and mature. This was achieved using a hierarchical integrated approach: first, Landsat-8 OLI imagery were used to map mature date palms in the study area; second, an object oriented classification (OOC) approach was applied at the plantation level using sub-meter Worldview-2 imagery (WV-2) to depict and map medium and young aged palms. Three age-stage categories of date palms were mapped with acceptable accuracy. The primary outcome of this classification approach was the creation of detailed maps of date palms to be used as input to a remote sensing (RS) based biomass estimation model for the assessment of the above ground biomass (AGB) and carbon sequestered (CS) of date palms. Results were validated using existing ancillary data and field checks. DP were mapped with an overall accuracy of 94.5% which was considered high in similar conditions of drylands, while the overall kappa statistics was estimated at 0.888.
EVALUATION OF ECOLOGICAL PROTECTION LEVEL UNDER THE FRAMEWORK OF TERRITORY SPATIAL PLANNING OF FUJIAN PROVINCE
Authors: Niu X. , Chen G. , Zhang D. , Zhang J. , Zhang J.
Published: August 2020

Abstract. A key mission of “the carrying capacity of natural resources and the suitability of territory spatial development evaluation” in China is to carry out the assessment of the ecological protection level, which is based on the ecosystem service functions level and ecological sensitivity level. The evaluation of ecological protection level is the basis for demarcating the ecological protection red line, which has become a major strategy to promote the construction of national ecological civilization. In this paper, taking the whole land area of Fujian province as an example and using the quantifying index method, based on remote sensing data including NPP, NDVI, and land use data, we first assess the ecosystem service functions level and ecological sensitivity level, combined with the existing nature reserves and national forest parks in Fujian province, and then evaluate the ecological protection level. The result shows that, the extremely important ecological protection area is 37,134.68 km2, accounting for 30.59% of total study area; the area of farmland located in the extremely important ecological protection area is 2,191.56 km2, making up 14.44% of the total farmland area; the area of construction land within the extremely important ecological protection area is 542.65 km2, accounting for 12.94% of the total construction land area.
HIGH-RESOLUTION OPTICAL SATELLITE IMAGES COLOR CONSISTENCY METHOD BASED ON EXTERNAL COLOR REFERENCES
Authors: Cui H. , Zhang G.
Published: August 2020

Abstract. Affected by factors such as season, illumination, atmospheric and sensor distortion, different satellite images often show obvious color difference, resulting in “stitching seams” at the edge of adjacent images, which seriously affects the application of satellite images. This study proposes a novel color consistency method for optical satellite images utilizing external color reference. Firstly, we improved the dark channel defogging method combining with the atmospheric distribution characteristics of satellite images, and used it to perform atmospheric correction on satellite images; Secondly, we corrected the color of atmospheric corrected satellite images through low-frequency signal replacement. Finally, we use a linear model to establish the relationship between high and low frequency signals, and stretching the high-frequency signal of images through local modelling. We selected two sets of representative experimental data for experiments, both the visual and quantitative obtained excellent results.
SCENE CLASSIFICATION BASED ON THE INTRINSIC MEAN OF LIE GROUP
Authors: Xu C. , Zhu G. , Yang K.
Published: August 2020

Abstract. Remote Sensing scene classification aims to identify semantic objects with similar characteristics from high resolution images. Even though existing methods have achieved satisfactory performance, the features used for classification modeling are still limited to some kinds of vector representation within a Euclidean space. As a result, their models are not robust to reflect the essential scene characteristics, hardly to promote classification accuracy higher. In this study, we propose a novel scene classification method based on the intrinsic mean on a Lie Group manifold. By introducing Lie Group machine learning into scene classification, the new method uses the geodesic distance on the Lie Group manifold, instead of Euclidean distance, solving the problem that non-euclidean space samples could not be calculated by Euclidean distance directly. The experiments show that our method produces satisfactory performance on two public and challenging remote sensing scene datasets, UC Merced and SIRI-WHU, respectively.
A STUDY ON THE COUPLING RELATIONSHIP BETWEEN BASIC PUBLIC SERVICES AND MULTI-DIMENSIONAL POVERTY IN RURAL POOR AREAS – EMPIRICAL ANALYSIS BASED ON HECHI CITY, GUANGXI
Authors: Wan Y. , Wang Y. , Gong Z. , Duan F. , Deng L.
Published: August 2020

Abstract. With the orderly promotion of the national poverty alleviation work, the number of rural poor people in China has decreased significantly, but due to the imbalance of regional development, deep poverty areas still exist.The balanced development of rural basic public services (RBPS) is one of the important directions to solve the deep-seated contradictions in poor areas. In this paper, Hechi City of Guangxi Province is taken as the research area, and the multi-dimensional poverty measurement model and RBPS evaluation model are constructed respectively. The collaborative development relationship between RBPS and multi-dimensional poverty reduction in the research area is revealed by coupling coordination degree and GIS spatial analysis method. The results show that the spatial distribution of coupling degree and coupling coordination degree between basic public services and multi-dimensional poverty is unbalanced. Basic public services and multi-dimensional poverty are closely related, and the level of basic public services has a positive impact on multi-dimensional poverty, and the poverty reduction of basic public services is feasible. In order to achieve stable and sustainable poverty eradication, it is necessary to establish a scientific and systematic evaluation system of rural basic public service poverty reduction.
LAND USE LAND COVER CHANGES AND THEIR IMPACTS ON ECOSYSTEM SERVICES IN THE NZHELELE RIVER CATCHMENT, SOUTH AFRICA
Authors: Nyathi N. A. , Zhao W. , Musakwa W.
Published: August 2020

Abstract. Land use change can result in variations in ecosystem services (ESS) and their relationships. Studying the temporal dynamics of ESS and their relationships can support scenario analyses that provide the theoretical basis for policy decisions and regional ecosystem management in any context. Understanding the spatiotemporal changes in land use and land cover change helps understand ESS management. In this study, the InVEST model was applied to assess carbon sequestration from 1999 to 2018 and to construct two simulated scenarios that represented different land use strategies. The results showed a spatial increase in the cropland class from the stipulated years with a corresponding increase in carbon within the area. It is assumed that the relationship between these two phenomena can affect agricultural policies as a large portion of South Africa depends on it for livelihood betterment. The Spearman’s Correlation Coefficient was used to assess the relationship between the two ESS. The result showed a highly significant correlation that means a change in policy from a governmental level is required. This paper subtly aims to provide data towards the South African context and more scenarios and research is needed to fully deduce effective land use management policies and decisions.
COLLAPSED BUILDING CLASSIFICATION WITH OPTICAL AND SAR DATA BASED ON MANIFOLD LEARNING
Authors: Ding L. , Miao H.
Published: August 2020

Abstract. The collapse of buildings is a major factor in the casualties and economic losses of earthquake disasters, and the degree of building collapse is an important indicator for disaster assessment. In order to improve the classification of collapsed building coverings (CBC), a new fusion technique was proposed to integrate optical data and SAR data at the pixel level based on manifold learning.Three typical manifold learning models, namely, Isometric Mapping(ISOMAP), Local Linear Embedding (LLE) and principle component analysis (PCA), were used, and their results were compared. Feature extraction were employed from SPOT-5 data with RADARSAT-2 data. Experimental results showed that 1) the most useful features of the optical and SAR data were contained in manifolds with low-intrinsic dimensionality, while various CBC classes were distributed differently throughout the low- dimensionality spaces of manifolds derived from different manifold learning models; 2) in some cases, the performance of Isomap is similar to PCA, but PCA generally performed the best in this study, yielding the best accuracy of all CBC classes and requiring the least amount of time to extract features and establish learning; and 3) the LLE-derived manifolds yielded the lowest accuracy, mainly by confusing soil with collapsed building and rock. These results show that the manifold learning can improve the effectiveness of CBC classification by fusing the optical and SAR data features at the pixel level, which can be applied in practice to support the accurate analysis of earthquake damage.
ANT COLONY OPTIMIZATION PARAMETER SELECTION FOR SHORTEST PATH PROBLEM
Authors: Zarrinpanjeh N. , Dadrass Javan F. , Azadi H. , De Maeyer P. , Witlox F.
Published: August 2020

Abstract. The shortest path problem has been studied to be solved through diverse deterministic and also stochastic approaches such as Ant Colony Optimization. One of the most challenging issues with the implication of Ant Colony Optimization to solve the shortest path problem is parameter selection and tuning which is found crucial to improve the computational performance of problem-solving. To tune parameters, it is vital to observe the response of each parameter to different values and study their effect on the final results. In this research, two experiments are designed and conducted to study the behavior of parameters in terms of generated results and computational performance. In the first experiment, evaporation, updating, and transition rule parameters are studied by iterative execution of shortest path generation between nodes considering different parameter values. In the second experiment, the number of initial ants is studied. Inspecting the results, it is observed that to avoid premature stagnation decreasing α value is recommended. On the other hand, ρ is observed to be considered for tuning of speed and number of diffusions of the algorithm. Moreover, it is realized that a high Q value would result in more correct results. Inspecting the initial number of ants, a threshold is realized where increasing the number of ants over this threshold would drastically result in more optimized paths.
OPPORTUNITIES AND CHALLENGES FOR AUGMENTED REALITY SITUATED GEOGRAPHICAL VISUALIZATION
Authors: Lobo M. J. , Christophe S.
Published: August 2020

Abstract. Augmented reality (AR) enables to display situated geographical visualizations, i.e visualizations that use virtual elements that are displayed in a geographical location. The place where the data is displayed complements the visualization. Many applications that take advantage of AR and situated visualizations exist, but they differ in the visualizations they present, their relationship to the geographic locations and goals. To better understand why and how AR based situated geovisualization is used, we review 45 papers coming from Human Computer Interaction, Visualization and Geographical Information Science venues that present such applications. Inspired by existing classifications, we characterize these papers according to the data they visualize and the geographical distance between the visualization and the data the visualization represents. This analysis reveals existing opportunities for situated geovisualization applications using AR.
3D CITY MODELS FOR URBAN MINING: POINT CLOUD BASED SEMANTIC ENRICHMENT FOR SPECTRAL VARIATION IDENTIFICATION IN HYPERSPECTRAL IMAGERY
Authors: Ruben P. A. , Sileryte R. , Agugiaro G.
Published: August 2020

Abstract. Urban mining aims at reusing building materials enclosed in our cities. Therefore, it requires accurate information on the availability of these materials for each separate building. While recent publications have demonstrated that such information can be obtained using machine learning and data fusion techniques applied to hyperspectral imagery, challenges still persist. One of these is the so-called ’salt-and-pepper noise’, i.e. the oversensitivity to the presence of several materials within one pixel (e.g. chimneys, roof windows). For the specific case of identifying roof materials, this research demonstrates the potential of 3D city models to identify and filter out such unreliable pixels beforehand. As, from a geometrical point of view, most available 3D city models are too generalized for this purpose (e.g. in CityGML Level of Detail 2), semantic enrichment using a point cloud is proposed to compensate missing details. So-called deviations are mapped onto a 3D building model by comparing it with a point cloud. Seeded region growing approach based on distance and orientation features is used for the comparison. Further, the results of a validation carried out for parts of Rotterdam and resulting in KHAT values as high as 0.7 are discussed.
A REGRESSION MODEL OF SPATIAL ACCURACY PREDICTION FOR OPENSTREETMAP BUILDINGS
Authors: Maidaneh Abdi I. , Le Guilcher A. , Olteanu-Raimond A-M.
Published: August 2020

Abstract. Data quality assessment of OpenStreetMap (OSM) data can be carried out by comparing them with a reference spatial data (e.g authoritative data). However, in case of a lack of reference data, the spatial accuracy is unknown. The aim of this work is therefore to propose a framework to infer relative spatial accuracy of OSM data by using machine learning methods. Our approach is based on the hypothesis that there is a relationship between extrinsic and intrinsic quality measures. Thus, starting from a multi-criteria data matching, the process seeks to establish a statistical relationship between measures of extrinsic quality of OSM (i.e. obtained by comparison with reference spatial data) and the measures of intrinsic quality of OSM (i.e. OSM features themselves) in order to estimate extrinsic quality on an unevaluated OSM dataset. The approach was applied on OSM buildings. On our dataset, the resulting regression model predicts the values on the extrinsic quality indicators with 30% less variance than an uninformed predictor.
MULTI-TEMPORAL SAR IMAGE DESPECKLING BASED A CONVOLUTIONAL NEURAL NETWORK
Authors: Zhou C. , Li J. , Shen H. , Yuan Q.
Published: August 2020

Abstract. Speckle noise is an intrinsic property of Synthetic Aperture Radar (SAR) imagery, which affects the quality of image. Single-temporal despeckling methods usually pay attention to the utilization of spatial information, but sometimes due to lack of sufficient information, the despeckling image is too smooth or losses some information about edge details. However, multi-temporal SAR images can provide extra information for despeckling resulting in better performance. Therefore, in this paper, we proposed a novel multi-temporal SAR despeckling method based a convolutional neural network (MSAR-CNN) embedded temporal and spatial attention (TSA) module to deeply mine the spatial and temporal correlation of multitemporal SAR images. The whole network, which is end-to-end trained with simulate realistic SAR data, consists of several residual blocks. In addition, the simulated and real-data experiments demonstrate that the proposed MSAR-CNN outperforms most of the mainstream methods in both the quantitative evaluation indexes and visual effects.
Predicting power outages caused by extratropical storms
Authors: Tervo Roope , Láng Ilona , Jung Alexander , Mäkelä Antti
Published: August 2020

Abstract. Strong winds induced by extratropical storms cause a large number of power outages especially in highly forested countries such as Finland. Thus, predicting the impact of the storms is one of the key challenges for power grid operators. This article introduces a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with forest inventory. We start by identifying storm objects from wind gust and pressure fields by using contour lines of 15 m s−1 and 1000 hPa respectively. The storm objects are then tracked and characterized with features derived from surface weather parameters and forest vegetation information. Finally, objects are classified with a supervised machine learning method based on how much damage to the power grid they are expected to cause. Random Forest Classifier, Support Vector Classifier, Naive Bayes, Gaussian Processes, and Multilayer Perceptron were evaluated for the classification task, Support Vector Classifier providing the best results.
Observation of an optical anisotropy in the deep glacial ice at the geographic South Pole using a laser dust logger
Authors: Rongen Martin , Bay Ryan Carlton , Blot Summer
Published: August 2020

Abstract. We report on a depth-dependent observation of a directional anisotropy in the recorded intensity of backscattered light as measured by an oriented laser dust logger. The measurement was performed in a drill hole at the geographic South Pole about a kilometer away from the IceCube Neutrino Observatory. The drill hole has remained open for access since the SPICEcore collaboration retrieved a 1751 m ice core. We find the anisotropy axis of 126±3∘ as measured below 1100 m to be compatible with the local flow direction. The observation is discussed in comparison to a similar anisotropy observed in data from the IceCube Neutrino Observatory and favors a birefringence-based scenario over previously suggested Mie-scattering-based explanations. In the future, the measurement principle, when combined with a full-chain simulation, may have the potential to provide a continuous record of fabric properties along the entire depth of a drill hole.
Vakarų Lietuvos jaunimo pritraukimas į Klaipėdos miestą: situacija ir perspektyvos / Attracting Youth from Western Lithuania to Klaipėda City: Situation and Perspectives
Authors: Naujokienė Aušra , Verkulevičiūtė-Kriukienė Daiva
Published: August 2020

Summary

Klaipėda is losing economically active, educated people due to migration, therefore the port city is characterized by “brain drain”. In addition, Klaipėda city population is rapidly aging. Due to the lack of labour resources and their quality, further economic and social development of the city becomes problematic.The largest proportion of young people who come to live in Klaipėda is from Klaipėda County (40.8 %), Tauragė County (36 %) and Telšiai County (23.2 %). According to the survey of young population originating from Klaipėda city and Western Lithuania, their perspectives and opportunities in Klaipėda were determined. More than half of pupils of the port city think that Klaipėda is attractive and as many as 42.6 % of them plan to live in the port city. If the aim is to keep young people in Klaipėda, they must be included in the port city life. There must be enough jobs in the city for people with different levels of education. There is also a need for more cultural events that are affordable not only for high-income people but also for pupils or young people who are starting their lives in the city. In addition, it is important that the city is safe to live, study and work.

Keywords: youth, Klaipėda city, attractiveness.
Tapelių ežero morfometrija ir baseino fizinės geografinės ypatybės / Morphometry of Lake Tapeliai and Physicalgeographical Characteristics of its Catchment
Authors: Pileckas Marijus , Žiliūtė Gražina
Published: August 2020

Depth measurements of Lake Tapeliai (located in Vilnius, Lithuania) were taken in February 2019. At the same time, the shoreline of the lake was revised. Measurements were made from ice in 767 spots. Depth measurement accuracy up to 0,05 m, accuracy of spot coordinates and water surface elevation measurement using GNSS device Topcon Hiper SR up to 1–2 cm. Later, a detailed (1 x 1 m) digital lake bottom model (DEM) was developed, a bathymetric plan of the lake was created, the main morphometric features were calculated, the boundaries and area of the lake catchment were adjusted, and the physi cal-geographical characteristics of the lake and its catchment were examined based on various data. Morphometric features of Lake Tapeliai measured and calculated in 2019 are as follows: coordinates of mean center 54.774378, 25.4468 (WGS), water surface elevation 136.48 m (in Height System LAS07 of Lithuania), surface area 13.14 ha, shoreline length 1689 m, maximum length 687 m, maximum width 295 m, mean width 191 m, shoreline development 1.31, maximum depth 9.45, mean depth 4.36, volume 573.8 thousands m3, mean width of littoral zone 17,4 m, catchment area (including the lake itself) 2,93 km2. Lake Tapeliai catchment is located in the moraine and limnoglacial plains of Vilija, it is characterized by a rather diverse relief, which consists of a section of Tapeliai glacial tunnel valley, limnoglacial and fliuvioglacial plains, aeolian landforms and moraine hills. Average annual precipitation is ~686 mm. Significant portion (45 %) of the annual precipitation replenishes the lake, mostly through groundwater discharge. Water residence time in the Lake Tapeliai is 0.63 years. Lake Tapeliai covers 4.5 % of the catchment area. Forests cover as much as 79.4 % of the catchment area, pine forests predominate (82.3 %). Built-up areas occupy 11.3 % of the catchment area. The predominantly sandy soils in the catchment area result in abundant groundwater inseeping, which is reflected in the springs found at the bottom of the lake. Abundant groundwater inseeping also reduces lake water level fluctuations, whose estimated amplitude from June 2018 to May 2020 reached just 21 cm.

Keywords: Tapeliai Landscape Reserve, Tapeliai, Lake, Vilnius, Lithuania, bathymetric chart, morphometry.
Notas sobre el paganismo en Kierkegaard
Authors: Viñas Vera Ángel
Published: August 2020

En el presente texto se muestran la idea de paganismo de Kierkegaard. Utilizamos toda la obra editada en vida por el autor, tanto la obra llamada pseudónima como la firmada con su propio nombre. En ella descubrimos que el término paganismo se dice de tres maneras: el paganismo del que vive en el mundo sin Dios, el paganismo cristiano y por último el paganismo de Sócrates. Al mostrar la riqueza del planteamiento sobre el paganismo descubriremos que esta idea no se define esencialmente por su adhesión a una u otra religión concreta o de algún momento de la historia, sino al modo de vivirse la existencia y la relación con el Dios. Por eso, la idea de paganismo no es necesariamente algo indeseable para un supuesto cristiano luterano del siglo XIX. Hasta tal punto que Kierkegaard dice que lo que necesita verdaderamente Dinamarca, y podríamos extenderlo a Europa hoy, es un nuevo Sócrates.
Representación de género en la comunicación en Twitter de la Selección Española de Fútbol
Authors: Abuín-Penas Javier , Fontenla-Pedreira Julia
Published: August 2020

Twitter es una herramienta que permite a las organizaciones deportivas comunicarse con sus públicos sin la necesidad de recurrir a los medios tradicionales. Tanto los clubes, las selecciones nacionales o los propios deportistas tienen un gran impacto en la sociedad actual. Este estudio analizó la representación de género durante la Copa Mundial de la FIFA 2018 y la Copa Mundial Femenina de la FIFA 2019. El análisis se centró en los mensajes publicados en Twitter por las cuentas oficiales de la Selección Española (@SeFutbol y @SeFutbolFem). Los resultados muestran una actividad, tratamiento y participación desigual, lo que pone de manifiesto la distancia todavía existente para conseguir la igualdad en el mundo deportivo, a pesar de las posibilidades que ofrecen las redes sociales.
Análisis del anuncio de la equiparación de premios de la World Surf League en 2018 en las noticias digitales españolas
Authors: Tena Perez Tania
Published: August 2020

En septiembre de 2018 y tras diversas polémicas, la World Surf League (WSL) notificó que iba a igualar la cuantía económica de los premios de todos sus eventos para hombres y mujeres. En el presente artículo, partimos de un análisis histórico de la desigualdad de género en el deporte para estudiar, desde una perspectiva feminista, la difusión y crítica de la noticia en los diferentes medios de comunicación online españoles, tanto generalistas como especializados, con el objetivo de analizar la repercusión que ha tenido un acontecimiento tan relevante para la igualdad en el deporte.
Patrocinio deportivo femenino. Situación actual y tendencias
Authors: Torres-Romay Emma , García-Mirón Silvia
Published: August 2020

El patrocinio deportivo sigue siendo una de las fórmulas de comunicación fundamentales en lo relativo a la Responsabilidad Social de las empresas. En los últimos años los éxitos deportivos femeninos parecen haber ido de la mano del aumento de los patrocinios aunque se ha confirmado como esos patrocinios suponen una inversión económica inferior a la que se realiza para el deporte masculino. En nuestro estudio realizamos un seguimiento de las principales empresas patrocinadoras en lo relativo al deporte femenino para poder valorar cómo gestionan este recurso y cómo se plasma en sus estrategias de comunicación. Además de esto, el análisis de contenido de esos patrocinios nos permitirá identificar tendencias e incluso los problemas que pueden identificarse al respecto.
INFANCY WITHIN ADVERTISING PLATFORM: YOUNG CHILDREN EXPERIENCES ON A VIDEO-SHARING WEBSITE.
Authors: Aggio Amanda
Published: August 2020

This paper investigates how young children experience digital advertising platforms. Specifically, it focuses on young children's participation in the YouTube app as part of an advertising mechanism that captures and profits from their views and attention. An innovative trans-disciplinary bridge between digital labour studies, biopolitics theory and qualitative research on children online has been developed to achieve this aim. The fact that children are going online progressively earlier raises critical questions around what they are experiencing in the virtual world. Data has become a way to profit and digital technology has become the infrastructure for capitalism permanence. This process of making a profit on user’s information leads to issues around trust and the confluence of surveillance and profit. It also raises questions around the persistence of Marxist concepts such as surplus labour, surplus value, and labour exploitation within the platform economy. Furthermore, in this environment one cannot disregard the relationship of power and the government of life; biopolitics should not be dissociable from capitalism. Thus, considering the early stage of young children’s cognitive development and their consequent vulnerability is urgent to understand how young children contribute to the political economy of the digital platform. The extent to which parents/caregivers and teachers are knowledgeable about the models of data mining, statistical profiling and corporate profit-generation that occur within this digital environment is also being investigated.
INTELLIGENT FAILURES: CLIPPY MEMES AND THE LIMITS OF DIGITAL ASSISTANTS
Authors: Baym Nancy , Shifman Limor , Persaud Christopher , Wagman Kelly
Published: August 2020

Often hated during its lifespan in product (1996-2006), Clippy – Microsoft’s Office Assistant, became a pop-culture icon in its afterlife. Delving into the plethora of memes featuring Clippy, we ask: why should a questionable character from a software program that has been out of use for well over a decade have so vibrant an afterlife? If Clippy has become a rhetorical resource, what is it being used to do? We propose that Clippy’s dual status as the original natural-language digital assistant, one that fell critically short in its ability to actually assist, makes it an ideal vehicle for critique of today’s ubiquitous assistants. An analysis of 1,148 meme instances collected from five sites led to a twofold argument: First, Clippy humor relies on the contrast between types of intelligence; Clippy is often too good at one kind, while lacking in another. In particular, Clippy lacks interpersonal intelligence: it serves as a disruptive mediator between its user and the world, as well as other human beings.

Yet this failure in “knowing its limits” and adapting to its environment is also what gives Clippy character. This suggests that digital assistants must attend to multiple kinds of intelligences; attending to any one over others may create an endearing character but not an effective digital assistant. Furthermore, the fact that the unbending yet personality-filled character of Clippy remains ungendered or male gives us insight into the pliant and empty characters of the female gendered Alexa, Siri, and Cortana.
“HEY, I LIKE YOUR VIDEOS. RELATE MUCH!”LOCATING SISTERHOOD IN A POSTCOLONIAL PUBLIC ON YOUTUBE
Authors: Cabalquinto Earvin Charles Borja , Soriano Cheryll
Published: August 2020

As part of a broader project that seeks to investigate the brokering of digitally-mediated intimacies through matchmaking platforms and social media channels, this paper unpacks the formation of ‘online sisterhood’ in a postcolonial intimate public, as evinced in the comments of viewers on selected YouTube videos of Rhaze, a Filipina YouTuber who is married to an Australian man. With a massive following of over 450 thousand followers, Rhaze’s videos typically receive diverse comments from her viewers and subscribers. This exposition is facilitated by collecting, categorising and analysing selected comments from Rhaze’s top videos. The comments were analysed through discourse analysis, paying special attention to the factors that influence digital media practices. The findings reveal that competing comments are shaped by postcolonial views on a gendered, racialized and class-based body in an interracial relationship. We then coin the term ‘online sisterhood’, reflecting the shared support that women nurture with other women through online practices. Ultimately, online sisterhood displays how Filipino women married to a white foreign national generate and negotiate spaces of mutual support in a neoliberal state. Paradoxically, a neoliberal government benefits from such cross-border and mediated mobility of Filipina migrants through the commodification of their everyday life. It is through this point that we argue for a closer evaluation of the role of ‘online sisterhoods’ in the construction of female subjectivity and imaginaries of mobility in the Global South.
THE IMPACT OF ATTITUDES TOWARDS GOVERNMENT AND CORPORATIONS ON TRUST IN TECHNOLOGY
Authors: Chen Yi-Ning Katherine , Wen Chia-Ho Ryan
Published: August 2020

Understanding public distrust of technology is both theoretically and practically important, yet while previous research has focused on the association between political ideology and trust in science, it is at best an inconsistent predictor. This study shall demonstrate that two dimensions of political ideology, attitudes towards governments and corporations, can more precisely predict trust in technology across issues. We will conduct an online survey on the science of radio frequency electromagnetic fields (RF-EMF) and Artificial Intelligence (AI) applications to test our hypotheses that trust in technology varies across issues and that attitudes towards government and corporations are important predictors of this trust.
CULTURAL COSMOLOGIES OF THE INTERNET: SITUATING DIGITAL NETWORKED TECHNOLOGIES IN DIVERSE MORAL UNIVERSES
Authors: Maddox Alexia , Sinanan Jolynna , Carter Marcus , Horst Heather , Spencer Michaela , Wiesenfeldt Gerhard
Published: August 2020

In this panel we consider how social actors situate uses of technologies within systems of moral norms and values while at the same time compelling the creation of new ones. Popular discourse tends to present dualistic thinking of the positive and negative impacts of technologies. Scholars have engaged with the internet and digital media, emphasising emancipatory subcultures (Coleman 2014; Gehl 2016, 2018) or presenting a critical view of the constraining aspects of networked technologies (Fish & Follis 2019; Fuchs 2014; Lovink 2016). These approaches are complimented by scholarship that considers technological practices and how they are embedded in social and cultural cosmologies (Burrell 2012; Horst & Foster 2018; Miller et. al. 2016). We argue for a closer integration of these bodies of scholarship through an examination of the contentious moral economies operating in emergent social spaces. The panel interrogates the relationship that social, political and economic actors have between their own ideas about what is good, appropriate and right and the diversity of orientations towards trust in techno-bureaucratic systems. We draw attention to immaterial systems and consider the social relationships and individual and collective imaginations that shape the production and experience of networked technologies. Through the papers, we articulate the forms of negotiation, resistance and refusal that occur when diverse moral universes, techno-regulating systems, and the conditions in which people find themselves collide.
ONLINE TRUST IN THE CONTEXT OF GLOBAL MIGRATION: MOBILITY, SOCIALITY, AND THE PRODUCTION OF CHINESE DIASPORIC SUBJECTIVITY IN AUSTRALIA
Authors: Wang Wilfred Yang , Zhao Xinyu , Chen Xu , Yang Yanan Jana
Published: August 2020

In light of the conference theme, Trust in the system, this panel brings together three papers that explore the (trans)formation of Chinese diasporic subjectivity through the intellectual lens of online dis/trust. As Gidden (2010) argues, trust is a shared social reality. Such a sense of collectively is being ‘stretched’ across national borders and cultural boundaries. Fewer explore the dis/trust and the associated concepts of authenticity and credibility against a transnational and cross-border environment. By transnationality, we refer to the increased level of mobility of the material goods, financial capitals and social networks of contemporary migrants. In other words, they live a life that is constantly ‘transiting’ between national, social and cultural borders rather than having to choose a static sense of belonging.

The three papers are then, organised to explore the transnational characters of Chinese migrants’ lives in Australia, from financial and economic survival to dating and socialisation, and the re-exploration of selfhood and belonging at later life. The three papers draw on different research methods range from ethnographic interviews and participant observation to the online walkthrough method and interface studies, and to the researcher embedded approach, to form critical inquiries about the production of trust in a digital era from the perspective of transnational migrations.

In examining the different stages of life and the plurality of Chinese migrants in Australia, this panel has the potential to contribute to the broader conversation in online trusts in a global, polymedia era.
RELIEF FROM COMMUNICATION: PARENTAL SURVEILLANCE TECHNOLOGIES, TRUST AND CARE
Authors: Damkjær Maja Sonne , Southerton Clare Victoria , Albrechtslund Anders
Published: August 2020

The everyday adoption of digital technologies such as mobile phones and social media has had transformative effects on interactions within the family (Clark, 2013), as families become increasingly dependent on their capacities for coordinating day-to-day activities and maintaining intimate relationships (Licoppe, 2004; Ling, 2014). Concurrently, these technologies enable new forms of surveillance, allowing parents to observe their children’s movements and interactions remotely, eg. via GPS-apps (Marx & Steeves, 2010), as well as lateral forms of surveillance embedded in social media practices like ‘Facebook stalking’ (Albrechtslund, 2013). This paper explores how the surveillant capacities of communication technologies are involved in shaping relations of trust in the family, drawing on empirical data from in-depth interviews with adolescents at two schools and 17 Danish families conducted during 2017. Despite surveillance often being represented as a practice which undermines trust (Mayer, 2003; Neyland, 2006; Rooney, 2010), our findings suggest that the relationship between trust and surveillance, for the families in our study, was far less straightforward. Surveillance was an important part of care practices for parents and, in some instances, tracking technologies were able to offer a kind of ‘relief’ from social pressures to remain in contact. This paper explores the perceptions of parents and adolescents regarding using communication technologies for surveillance, to examine the nuanced constitution of trust occurring.
“MISINFODEMICS”— UNPACKING THE CORE NARRATIVES OF MULTINATIONAL DRINK COMPANIES’ ONLINE MARKETING CAMPAIGNS AIMED AT YOUNG PEOPLE IN DEVELOPING COUNTRIES
Authors: Dugmore Harry
Published: August 2020

Multinational food and drink companies have increased their social media marketing budget and efforts and some have been rewarded with increased youth consumption of highly refined snack foods and Sugar-Sweetened Beverages (SSBs) even as overall consumption of SSBs, in many more developed countries, is falling. (Brand-Miller & Barclay, 2017; Chaloupka, Powell, & Warner, 2019). This strategy seems to be working particularly well in Africa. But at the same time, multinational companies are also waging more existential battles against a growing public awareness of the role their products play in epidemics of overweight and obesity (Du, Tugendhaft, Erzse, & Hofman, 2018; Nestle, 2018). This paper explores how ‘Big Food’ multinationals has tried to frame these debates around issues of ‘energy balance’ and highlight SSB companies’ role in promoting the exercise side of their ‘energy balance’ frame. (Ruskin, Stuckler, Serôdio, Barlow, & McKee, 2018, Nestle, 2018). This messaging, this paper argues, propagates misinformation, and is implicated in the current epidemic of poor nutrition in both developing (and developed) countries. Using both thematic content analysis, augmented with audience reception study through focus groups sessions, this paper explores how these companies’ social media marketing combines with their more traditional marketing channels to simultaneously sell product *and* defend their products right to be sold untaxed and unrestricted. The paper explores how these messages resonate with young adults in Nigeria and South Africa, and finds that the SSB companies' overall campaigns and particularly the social media components, are effective in countering public health messaging.
TRUST IN THE MUSIC? AUTOMATED MUSIC DISCOVERY, MUSIC RECOMMENDATION SYSTEMS & ALGORITHMIC CULTURE.
Authors: Sophie Olivia Freeman
Published: August 2020

In this paper I argue that music recommendation algorithms are a complex element of contemporary digital culture. We trust music streaming and recommender systems like Spotify to ‘set the mood’ for us, to soundtrack our private lives and activities, to recommend & discover for us. These systems purport to ‘know’ us (alongside the millions of other users), and as such we let them into our most intimate listening spaces and moments. We fetishise and share the datafication of our listening habits, reflected to us annually in Spotify’s “Your 2018 Wrapped” and every Monday in ‘Discover Weekly’, even daily in the “playlists made for you”. As the accuracy of these recommendations increases, so too does our trust in these systems. ‘Bad’ or inaccurate recommendations feel like a betrayal, giving us the sense that the algorithms don’t really know us at all. Users speak of ‘their’ algorithm, as if it belonged to them and not a part of a complex machine learning recommendation system. This paper builds on research which critically examined the music recommendation system that powers Spotify and its many discovery features. The research explored the process through which Spotify automates discovery by incorporating established methods of music consumption, and demonstrated that music recommendation systems such as Spotify are emblematic of the politics of algorithmic culture.
BANKING ON CULTURAL INTERMEDIARIES ACROSS WEBTOON, WEBNOVEL AND VIDEO-SHARING PLATFORMS IN ASIA’S DIGITAL CREATIVE ECONOMY
Authors: Yecies Brian , Ren Xiang (Tony) , Shim Aegyung , Wang Dingkun
Published: August 2020

This panel investigates how complex layers of trust and (dis)trust are surrounding and impacting on the fans, also known as ‘cultural intermediaries’, involved in the production, circulation, translation and remake of Korean and Chinese webtoon and webnovel platforms in Asia and among Asian users. Collectively, the panellists argue for a reconceptualisation of the concept of ‘Internet platform’. In so doing, we interrogate the concepts of ‘platformization’, ‘platform capitalism’ and ‘digital capitalism’ by asking: how, and with what effect, Korean and Chinese digital platforms – as well as their aggregated domestic and international users, are operating in the Asia Pacific, compared to more global ‘liberal’ platforms? Noting the activities of ‘digital champions’, such as the giant Korean search portal Naver, as well as China’s Kuaikan and Bilibili enterprises, which are now rapidly emerging in the shadows of their larger competitors: iQiyi (Baidu), Taobao (Alibaba), QQ (Tencent), collectively known as BAT. In sum, we show which Korean and Chinese webtoon and webnovel platforms are taking root in various regional territories and among regional audiences. Our intent is to illustrate how digital platforms (i.e. the globality of the internet) are refashioning the image of Korea and China, which is often viewed outside of their national borders as driven by an ideologically-free ‘broadband nirvana’ (Goldsmith et al. 2011), and tainted by authoritarian state, respectively. Accordingly, all four papers will consider how platform capitalism offers new ways to understand the outreach of both Korean and Chinese digital culture – from both economic and technological viewpoints.