The wisdom of social multimedia

Jin, Xin; Gallagher, Andrew; Cao, Liangliang; Luo, Jiebo; Han, Jiawei

doi:10.1145/1873951.1874196

Cited by 98 publications

(6 citation statements)

References 14 publications

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“…Lately, with the evolution of Internet, several approaches have been developed for using the so-called big data (Jin et al, 2010) made available by the "social media" platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the perception of urban visual quality: an approach integrating big data and geostatistical techniques

et al. 2022

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Human well-being is affected by the design quality of the city in which they live and walk. This depends primarily on specific physical characteristics and how they are aggregated together. Many studies have highlighted the great potential of photographic data shared on the Flickr platform for analyzing environmental perceptions in landscape and urban planning. Other researchers have used panoramic images from the Google Street View (GSV) web service to extract data on urban quality. However, at the urban level, there are no studies correlating quality perceptions detected by social media platforms with spatial geographic characteristics through geostatistical models. This work proposes the analysis of urban quality in different areas of the Livorno city through a methodological approach based on Geographical Random Forest regression. The result offers important insights into the physical characteristics of a street environment that contribute to the more abstract qualities of urban design.

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“…Lately, with the evolution of Internet, several approaches have been developed for using the so-called big data (Jin et al, 2010) made available by the "social media" platforms.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the perception of urban visual quality: an approach integrating big data and geostatistical techniques

et al. 2022

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“…In contrast, the Boston Consulting Group used survey data to study employees' opinions regarding WFH owing to the COVID-19 pandemic [19]. However, social media data allow an opportunity for conducting a timelier study of many population-level issues on a larger scale [20]. We acquired data with an authorized Twitter developer account using Tweepy.…”

Section: Study Objectivesmentioning

confidence: 99%

Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study

Xiong¹,

Пин²,

Lyu³

et al. 2021

JMIR Med Inform

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Background Since March 2020, companies nationwide have started work from home (WFH) owing to the rapid increase of confirmed COVID-19 cases in an attempt to help prevent the disease from spreading and to rescue the economy from the pandemic. Many organizations have conducted surveys to understand people’s opinions toward WFH. However, the findings are limited owing to a small sample size and the dynamic topics over time. Objective This study aims to understand public opinions regarding WFH in the United States during the COVID-19 pandemic. Methods We conducted a large-scale social media study using Twitter data to portray different groups of individuals who have positive or negative opinions on WFH. We performed an ordinary least squares regression analysis to investigate the relationship between the sentiment about WFH and user characteristics including gender, age, ethnicity, median household income, and population density. To better understand the public opinion, we used latent Dirichlet allocation to extract topics and investigate how tweet contents are related to people’s attitude. Results On performing ordinary least squares regression analysis using a large-scale data set of publicly available Twitter posts (n=28,579) regarding WFH during April 10-22, 2020, we found that the sentiment on WFH varies across user characteristics. In particular, women tend to be more positive about WFH (P<.001). People in their 40s are more positive toward WFH than those in other age groups (P<.001). People from high-income areas are more likely to have positive opinions about WFH (P<.001). These nuanced differences are supported by a more fine-grained topic analysis. At a higher level, we found that the most negative sentiment about WFH roughly corresponds to the discussion on government policy. However, people express a more positive sentiment when discussing topics on “remote work or study” and “encouragement.” Furthermore, topic distributions vary across different user groups. Women pay more attention to family activities than men (P<.05). Older people talk more about work and express a more positive sentiment regarding WFH. Conclusions This paper presents a large-scale social media–based study to understand the public opinion on WFH in the United States during the COVID-19 pandemic. We hope that this study can contribute to policymaking both at the national and institution or company levels to improve the overall population’s experience with WFH.

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“…At such overwhelming scales, social media is certainly having a pervasive influence on the society. Social media help people and businesses stay better connected, better informed [2] [3], and also can serve as distributed social sensors and source of wisdom of crowds [4] [5] [6].…”

Section: Introductionmentioning

confidence: 99%

Browsing Information Overloading Unstructured Multimedia Social Network Contents on Mobile Devices

Chen¹

2016

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This paper addresses important technical issues in browsing heterogeneous unstructured multimedia feeds on consumer mobile devices derived from social network contents. We will first present several pressing technical challenges associated with creating a browsing system that can summarize information overloading unstructured social media feeds and produce a novel GIST, namely, Graphical Intelligent Semantic Transform, for effective and visually pleasing browsing on a mobile device by the social media users. We will then illustrate innovative solutions to solving a suite of interdisciplinary problems associated with developing such a system. Preliminary results will be shown to demonstrate the feasibility of creating such a GIST for browsing information overloading social media feeds on consumer mobile devices.

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The wisdom of social multimedia

Cited by 98 publications

References 14 publications

Assessing the perception of urban visual quality: an approach integrating big data and geostatistical techniques

Assessing the perception of urban visual quality: an approach integrating big data and geostatistical techniques

Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study

Browsing Information Overloading Unstructured Multimedia Social Network Contents on Mobile Devices

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