Visual Analysis for Messages in Social Media

2019 ◽  
Author(s):  
Mengyang Zhang ◽  
Kaokao Lv ◽  
Liang Tang ◽  
Chuanming Huang ◽  
Zhaokang Yuan ◽  
...  
Keyword(s):  
Social Media ◽  
Visual Analysis

Responding to #yogabody on Instagram

Screen Bodies ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 117-125
Author(s):  
Bilge Gölge
Keyword(s):  
Social Media ◽  
New Media ◽  
Visual Analysis ◽  
Modern Society ◽  
The Body ◽  
Self Identity ◽  
New Era ◽  
Self Actualization ◽  
Modern Era ◽  
Late Modern

This article focuses on representations of the yoga body on social media, explaining what the female body in an asana pose stands for in consideration of the dichotomy between Foucault’s docile body controlled by the technology of power and Anita Seppä’s “aestheticization of the subject” as a means of resistance. While socio-technological changes have introduced a new context in the modern era, the dominance of seeing and visual culture has remained central in late-modern society. Through social media, we have entered a new era of constructing self-identity in relation to gender and the body. Looking into the relationship between asana practice and self-identity in postural yoga, I investigate the imaged bodies of yoginis that function under the control of power and as a technique for self-actualization. Drawing from a visual analysis of Instagram posts and interpreting the bodily practices of yoginis, I will search for what happened to modernity’s docile body in the context of this new media.

scholarly journals The symbol of social media in contemporary protest: Twitter and the Gezi Park movement

2020 ◽  
pp. 135485652093374
Author(s):  
Olu Jenzen ◽  
Itir Erhart ◽  
Hande Eslen-Ziya ◽  
Umut Korkut ◽  
Aidan McGarry
Keyword(s):  
Social Media ◽  
Social Movement ◽  
Information Sharing ◽  
Digital Media ◽  
Collective Identity ◽  
Visual Analysis ◽  
Main Emphasis ◽  
Media Practices

This article explores how Twitter has emerged as a signifier of contemporary protest. Using the concept of ‘social media imaginaries’, a derivative of the broader field of ‘media imaginaries’, our analysis seeks to offer new insights into activists’ relation to and conceptualisation of social media and how it shapes their digital media practices. Extending the concept of media imaginaries to include analysis of protestors’ use of aesthetics, it aims to unpick how a particular ‘social media imaginary’ is constructed and informs their collective identity. Using the Gezi Park protest of 2013 as a case study, it illustrates how social media became a symbolic part of the protest movement by providing the visualised possibility of imagining the movement. In previous research, the main emphasis has been given to the functionality of social media as a means of information sharing and a tool for protest organisation. This article seeks to redress this by directing our attention to the role of visual communication in online protest expressions and thus also illustrates the role of visual analysis in social movement studies.

OpinionFlow: Visual Analysis of Opinion Diffusion on Social Media

2014 ◽  
Vol 20 (12) ◽  
pp. 1763-1772 ◽  
Author(s):  
Yingcai Wu ◽  
Shixia Liu ◽  
Kai Yan ◽  
Mengchen Liu ◽  
Fangzhao Wu
Keyword(s):  
Social Media ◽  
Visual Analysis

scholarly journals TOURISTS GEOVISUALIZATION ANALYSIS UTILIZING INSTAGRAM DATA IN CENTRAL JAVA PROVINCE AND SPECIAL REGION OF YOGYAKARTA

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 535-542
Author(s):  
A. Rofi’i ◽  
T. W. Wibowo ◽  
N. M. Farda ◽  
Keyword(s):  
Social Media ◽  
Big Data ◽  
Spatial Data ◽  
Visual Analysis ◽  
Data Extraction ◽  
Size Variation ◽  
Extraction Process ◽  
Tourist Attractions ◽  
Central Java ◽  
Special Region

Abstract. The growth of Indonesia‟s national economy in the sector of tourism has been improving constantly. Based on BPS data year 2015, tourism has contributed to PDB with the amount of 4,25%. Tourists is an important aspect because they play a role in the economic change in tourism. Along with social media development, tourists‟ distribution can be monitored using big data in social media. Instagram is one of the social media which is often used by tourists to share photos or videos while traveling. Issues that appeared when using big data Instagram to produce spatial data are size, variation, and a big time span. This research is aimed to extract big data Instagram to produce basic tourists’ spatial data and analyze tourist attractions using geovisualization hexagonal tessellation in West Java Province and Special Region of Yogyakarta. Generally, the methods used are divided into three which are data mining, graphic visual analysis and geovisualization classification hexagonal tessellation. The Instagram data extraction process uses a web-based software called Netlytic, while pre-processing data to produce tourists’ spatial data uses QGIS software. Hexagonal tessellation is tested by graphic visual to ensure the most effective measurement in the scale of 1 : 1.250.000. The most effective hexagonal tessellation measurement is used to classify tourist attractions. Based on the results, it shows that the most effective measurement of hexagonal tessellation is 2 Km. The most popular tourist attraction is Malioboro Yogyakarta based on hexagonal tessellation geovisualization analysis.

scholarly journals Participatory Social Sensor: A Framework to Social Media Data Acquisition and Analysis

2019 ◽  
Author(s):  
Igor Araujo ◽  
Paulo Henrique Lopes Rettore ◽  
João Guilherme Maia de Menezes
Keyword(s):  
Social Media ◽  
Data Acquisition ◽  
Visual Analysis ◽  
Social Behaviors ◽  
Data Access ◽  
Heterogeneous Data ◽  
Social Media Data ◽  
Analysis Process ◽  
Media Data ◽  
Social Sensor

Nowadays, understanding urban mobility, transit, people viewpoint, and social behaviors has been the focus of many research and investments. However, data access is restricted to private companies and governments. In addition, the costs to create a sensor infrastructure on a given area is prohibitive. Then, using Location-Based Social Media (LBSM) may provide a new way to better comprehend the social behaviors, by the use of a users viewpoint. In this work, we propose the use of LBSM as participatory sensing, designing the Participatory Social Sensor (PSS), a friendly framework to social media data acquisition and analysis. We develop the Twitter data acquisition and analysis process, aiming to achieve the user application goals through a file setup,where the user specifies the spatial area, temporal interval, tags, and other parameters. As a result, the PSS shows a set of visual analysis which provides a context overview, allowing an easy way to researchers make-decision. A case study, Detection and Enrichment Service for Road Events Based on Heterogeneous Data Merger for VANETs, based on PSS framework was published in the current conference.

scholarly journals Social media for health promotion: A visual analysis of “TB proof” South Africa's Facebook page

2020 ◽  
Vol 63 ◽  
pp. 101386
Author(s):  
Asongu Acha-Anyi ◽  
Paul N. Acha-Anyi ◽  
Simplice A. Asongu ◽  
Vanessa S. Tchamyou
Keyword(s):  
Social Media ◽  
Health Promotion ◽  
Visual Analysis

FlowSampler: Visual Analysis of Urban Flows in Geolocated Social Media Data

2015 ◽  
pp. 5-17 ◽  
Author(s):  
Alvin Chua ◽  
Ernesto Marcheggiani ◽  
Loris Servillo ◽  
Andrew Vande Moere
Keyword(s):  
Social Media ◽  
Visual Analysis ◽  
Social Media Data ◽  
Media Data

scholarly journals StanceVis Prime: visual analysis of sentiment and stance in social media texts

2020 ◽  
Vol 23 (6) ◽  
pp. 1015-1034
Author(s):  
Kostiantyn Kucher ◽  
Rafael M. Martins ◽  
Carita Paradis ◽  
Andreas Kerren
Keyword(s):  
Social Media ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Research Problem ◽  
Data Sources ◽  
Data Series ◽  
Text Documents ◽  
Document Collections ◽  
Social Media Data ◽  
Media Data

Abstract Text visualization and visual text analytics methods have been successfully applied for various tasks related to the analysis of individual text documents and large document collections such as summarization of main topics or identification of events in discourse. Visualization of sentiments and emotions detected in textual data has also become an important topic of interest, especially with regard to the data originating from social media. Despite the growing interest in this topic, the research problem related to detecting and visualizing various stances, such as rudeness or uncertainty, has not been adequately addressed by the existing approaches. The challenges associated with this problem include the development of the underlying computational methods and visualization of the corresponding multi-label stance classification results. In this paper, we describe our work on a visual analytics platform, called StanceVis Prime, which has been designed for the analysis of sentiment and stance in temporal text data from various social media data sources. The use case scenarios intended for StanceVis Prime include social media monitoring and research in sociolinguistics. The design was motivated by the requirements of collaborating domain experts in linguistics as part of a larger research project on stance analysis. Our approach involves consuming documents from several text stream sources and applying sentiment and stance classification, resulting in multiple data series associated with source texts. StanceVis Prime provides the end users with an overview of similarities between the data series based on dynamic time warping analysis, as well as detailed visualizations of data series values. Users can also retrieve and conduct both distant and close reading of the documents corresponding to the data series. We demonstrate our approach with case studies involving political targets of interest and several social media data sources and report preliminary user feedback received from a domain expert. Graphic abstract

scholarly journals Visual Analysis of Topic Competition on Social Media

2013 ◽  
Vol 19 (12) ◽  
pp. 2012-2021 ◽  
Author(s):  
Panpan Xu ◽  
Yingcai Wu ◽  
Enxun Wei ◽  
Tai-Quan Peng ◽  
Shixia Liu ◽  
...  
Keyword(s):  
Social Media ◽  
Visual Analysis
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