An Empirical Investigation on Social Media Users' Demand for Financial Information Distributed via Social Media Platforms

2018 ◽  
Vol 33 (2) ◽  
pp. 155-175 ◽  
Author(s):  
Robert N. Marley ◽  
Neal M. Snow
Keyword(s):  
Social Media ◽  
Information Content ◽  
Empirical Investigation ◽  
Financial Information ◽  
Social Media Platforms ◽  
User Groups ◽  
Media Communications ◽  
Social Media Presence ◽  
Using Data ◽  
Jel Classifications

ABSTRACT Managers feel significant pressure to establish a social media presence that differentiates their organization from rivals, though few managers feel confident that their organization provides social media users with the information they desire. Thus, while the supply of information provided to social media users by organizations continues to proliferate rapidly, few studies have investigated the information social media users want organizations to provide. This study explores the information desires of two social media user groups: non-professional investors and non-investors. We create and validate a social media information content taxonomy using data from three experiments, finding that the information desires of both groups are relatively similar. Specifically, social media users primarily want organizations to provide them with information that addresses them as customers and non-professional investors desire financial information more than non-investors. Across platforms, Facebook is the platform most closely associated with organizational social media communications. JEL Classifications: M31; M37; M41; G24; D83.

scholarly journals Property Valuation Using Linear Regression and Random Forest Algorithm

2021 ◽  
Vol 10 (4) ◽  
pp. 0-0
Keyword(s):  
Social Media ◽  
Urban Areas ◽  
Recent Past ◽  
Property Valuation ◽  
Nation States ◽  
Social Media Platforms ◽  
User Groups ◽  
Property Sales ◽  
Using Data ◽  
Economic Boom

The economic boom over the recent past and the quest to further develop, has made several nation states the business hubs in their regions. Along with the investments, there has been growth in the number of property sales. Social media has become convenient platform of choice for advertising property sales after the introduction of Web 2.0. This article utilizes social media platforms like Facebook to scrape data from user groups advertising properties and then using data mining techniques and approaches to determine true valuation of properties. This methodology is based on set attributes, in the urban areas by looking at the property sales of the recent past within the same area. This enables investors interested in these properties and provides a fair idea of price of properties based on the key attributes associated with the respective property.

scholarly journals Property Valuation Using Linear Regression and Random Forest Algorithm

2021 ◽  
Vol 10 (4) ◽  
pp. 1-16
Author(s):  
Sam Goundar ◽  
Akashdeep Bhardwaj
Keyword(s):  
Social Media ◽  
Urban Areas ◽  
Recent Past ◽  
Property Valuation ◽  
Nation States ◽  
Social Media Platforms ◽  
User Groups ◽  
Property Sales ◽  
Using Data ◽  
Economic Boom

The economic boom over the recent past and the quest to further develop, has made several nation states the business hubs in their regions. Along with the investments, there has been growth in the number of property sales. Social media has become convenient platform of choice for advertising property sales after the introduction of Web 2.0. This article utilizes social media platforms like Facebook to scrape data from user groups advertising properties and then using data mining techniques and approaches to determine true valuation of properties. This methodology is based on set attributes, in the urban areas by looking at the property sales of the recent past within the same area. This enables investors interested in these properties and provides a fair idea of price of properties based on the key attributes associated with the respective property.

scholarly journals Multi-Platform Social Media Use: Little Evidence of Impacts on Adult Well-Being

2020 ◽  
Author(s):  
Sophie Lohmann ◽  
Emilio Zagheni
Keyword(s):  
Social Media ◽  
Media Use ◽  
Scientific Evidence ◽  
General Social Survey ◽  
Well Being ◽  
Young Female ◽  
Social Media Use ◽  
Social Media Platforms ◽  
Data Source ◽  
Using Data

Social media have become a near-ubiquitous part of our lives. The growing concern that their use may alter our well-being has been met with elusive scientific evidence. Existing literature often simplifies social media use as a homogeneous process. In reality, social media use and functions vary widely depending on platform and demographic characteristics of users, and there may be qualitative differences between using few versus many different social media platforms. Using data from the General Social Survey, an underanalyzed data source for this purpose, we characterize intensive social media users and examine how differential platform use impacts well-being. We document substantial heterogeneity in the demography of users and show that intensive users tend to be young, female, more likely to be Black than Hispanic, from high SES backgrounds, from more religious backgrounds, and from families with migration background, compared to both non-users and moderate users. The intensity of social media use seemed largely unrelated to well-being in both unadjusted models and in propensity-score models that adjusted for selection bias and demographic factors. Among middle-aged and older adults, however, intensive social media use may be slightly associated with depressive symptoms. Our findings indicate that although mediums of communication have changed with the advent of social media, these new mediums are not necessarily detrimental to well-being.

scholarly journals Social Media Research Network: Social Media Toolkit

2021 ◽  
Author(s):  
Akash Shroff ◽  
Chantelle A Roulston ◽  
Marian Ruiz ◽  
Sharon Chen
Keyword(s):  
Social Media ◽  
Science Communication ◽  
Research Network ◽  
Research Groups ◽  
The Social ◽  
Large Audience ◽  
Social Media Platforms ◽  
Media Research ◽  
Social Media Research ◽  
Social Media Presence

The Social Media Research Network was co-founded by Chantelle Roulston and Akash Shroff in August 2021 with the support of Dr. Jessica Schleider and the Lab for Scalable Mental Health (LSMH). Since 2018, LSMH has been recruiting adolescents and parents using social media—primarily Facebook and Instagram. As of September 2021, our social media presence has reached 1.4 million people across the world. More than 35,000 individuals have interacted with our posts and messages and more than 6,000 youth, young adults, and parents have completed our single-session interventions. We wanted to share our current success and improve our processes by forming a collaboration of psychology/adolescent development research labs.The SMRN Social Media Toolkit is designed to consolidate social media experiences and suggestions from various labs into a useful document for others to use. This is by no means an exhaustive list of social media platforms and suggestions. We have limited the toolkit to include the use of Facebook and Instagram, owned and trademarked by Meta Platforms, Inc.. Instagram and Facebook encompass a very large audience (diverse in age, location, and race/ethnicity). The platforms have a lot of overlap and have been successful in research efforts for the authors. This toolkit outlines broad concepts of branding, post design, and post management. It also provides details, suggestions, and tips on how to create an account, gain a following, increase engagement, and more on both Facebook and Instagram. . Lastly, it details the process of using paid Facebook and Instagram advertisements for research purposes (i.e., recruiting participants).The ultimate goal of SMRN is to increase collaboration across research groups so that we can leverage the entire network’s social media presence to improve recruitment, science communication, and outreach efforts for all research groups involved. We hope this document will serve as a preliminary guide for the research groups within the network.

Social Media and Voluntary Nonfinancial Disclosure: Evidence from Twitter Presence and Corporate Political Disclosure

2018 ◽  
Vol 33 (2) ◽  
pp. 99-128 ◽  
Author(s):  
Lijun (Gillian) Lei ◽  
Yutao Li ◽  
Yan Luo
Keyword(s):  
Social Media ◽  
Econometric Model ◽  
Data Availability ◽  
Political Contributions ◽  
Cross Sectional ◽  
Political Activities ◽  
Social Media Platforms ◽  
Sectional Analysis ◽  
Jel Classifications ◽  
Nonfinancial Disclosure

ABSTRACT This study uses a sample of 1,316 firm-year observations of S&P 500 companies (2012–2016) to investigate whether and how social media (i.e., Twitter) affects firms' voluntary nonfinancial disclosure (i.e., corporate political disclosure). Our results show that Twitter-adopting firms are generally more transparent in their disclosure of corporate political contributions and of related policies and board oversight. Moreover, firms with more Twitter followers and firms whose corporate political activities are targeted in more Twitter messages are more transparent in such disclosures. Our cross-sectional analysis suggests that this effect is stronger for firms whose stakeholders are more active on Twitter and firms that are less visible or more reputable. Our results remain robust to different econometric model specifications and controlling for alternative social media platforms. Taken together, our findings suggest that social media (i.e., Twitter) presence exerts pressure on firms' voluntary nonfinancial disclosure practices (i.e., corporate political disclosure). JEL Classifications: G38; M41; M48. Data Availability: Data are available from the sources indicated in the text.

Deep Learning and Machine Learning Techniques for Analyzing Travelers' Online Reviews

2022 ◽  
pp. 20-39
Author(s):  
Elliot Mbunge ◽  
Benhildah Muchemwa
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Deep Learning ◽  
Hospitality Industry ◽  
Learning Models ◽  
Online Data ◽  
Social Media Platforms ◽  
Using Data ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Social media platforms play a tremendous role in the tourism and hospitality industry. Social media platforms are increasingly becoming a source of information. The complexity and increasing size of tourists' online data make it difficult to extract meaningful insights using traditional models. Therefore, this scoping and comprehensive review aimed to analyze machine learning and deep learning models applied to model tourism data. The study revealed that deep learning and machine learning models are used for forecasting and predicting tourism demand using data from search query data, Google trends, and social media platforms. Also, the study revealed that data-driven models can assist managers and policymakers in mapping and segmenting tourism hotspots and attractions and predicting revenue that is likely to be generated, exploring targeting marketing, segmenting tourists based on their spending patterns, lifestyle, and age group. However, hybrid deep learning models such as inceptionV3, MobilenetsV3, and YOLOv4 are not yet explored in the tourism and hospitality industry.

The Importance of Interactions Between Content Characteristics and Creator Characteristics for Studying Virality in Social Media

2020 ◽  
Vol 31 (2) ◽  
pp. 576-588
Author(s):  
Yue Han ◽  
Theodoros Lappas ◽  
Gaurav Sabnis
Keyword(s):  
Social Media ◽  
Conceptual Framework ◽  
Predictive Power ◽  
Brand Building ◽  
Social Media Presence ◽  
Using Data ◽  
Content Characteristics

Why does a social media post go viral? Two approaches to understand this mystery are content-based research and creator-based research. Both content characteristics and creator characteristics have been examined for their influence on virality. But the relationships between them are rarely discussed. We propose an extension to our existing conceptual framework to study the interactions between content and creator variables. And we demonstrate the significance of the interactions using data from 800,000 tweets. We find that by adding content-–creator interactions, the predictive power of the model improves significantly, which underlines the importance of the interactions for studying virality in social media. We also provide insights for managers on shaping their social media presence and strategy to use social media popularity for marketing and brand building.

scholarly journals Tourism trend and network analysis utilizing big data on social media

2018 ◽  
Vol 7 (2.12) ◽  
pp. 312
Author(s):  
Jae Woo Choi ◽  
Hye YoungKim
Keyword(s):  
Social Media ◽  
Big Data ◽  
Mutual Interaction ◽  
Tourism Promotion ◽  
Promotional Efforts ◽  
Social Media Platforms ◽  
Twitter Account ◽  
User Groups ◽  
Media Platform ◽  
Promotional Strategies

Background/Objectives: With evolving trends, tourism is also experiencing more diverse policies and methods of promotion. In particular, with the development and increasing popularity of social media platforms, a new trend is setting in. In line with such changes, the current study sets out to utilize big data on social media platforms to analyze trends in tourism, ways in which tourism elements mutually interact, and analyze patterns, in order to propose tourism promotion strategies and provide related basic data.Methods/Statistical analysis: Analysis on social media platforms were conducted to visually express relationship among nodes and analyze the structure and status of link in quantitative terms. NodeXL is an add-in program to Microsoft Excel; it allows the user to directly collect data from social media platforms to execute matrics, statistics, and visualization. The data was collected from Korea Tourism Organization (KTO)’s Twitter and Facebook accounts. Hashtags (#) on 3,200 posts on the Twitter account were analyzed to compute the tourism trend, and the inter-node interactions and links on the Facebook fan pages were analyzed in terms of network density and centrality to calculate the form and characteristics of social media networks.Findings: By analyzing social media pages that represent promotional efforts for Korean tourism, we were able to find the following results: On the KTO Twitter account, the higher hashtag terms were “eating tour,” and “exciting travel,” which follow the recent tourism trends. However, because of platform restrictions, the Twitter account, rather than engaging in mutual interactions with its users, only tended to deliver information, and was unable to reflect more diverse tourism trends. On Facebook, 348 nodes were actively linked 14.99 times on average, indicating a healthy level of activity. Average degrees of connection was 2.214, which is smaller than average connection distance of small societies, indicating efficient mutual interaction. There were three core user groups, with eleven individuals serving as media nodes, and six users with Eigenvector centrality.Improvements/Applications: Tourism promotion must be executed in line with diverse and latest trends in the field. Because Facebook has a higher level of mutual interaction than Twitter, the account holder can maximize the promotional effects by utilizing individuals that serve as the centrality node. That is to say that promotional strategies that take into account the characteristics of individual social media platform are required. 

This Is How We Do It: A Qualitative Approach to National Sport Organizations’ Social-Media Implementation

2017 ◽  
Vol 10 (2) ◽  
pp. 196-217 ◽  
Author(s):  
Michael L. Naraine ◽  
Milena M. Parent
Keyword(s):  
Social Media ◽  
Qualitative Approach ◽  
Sport Organizations ◽  
Factors Affecting ◽  
Perceived Utility ◽  
Strategic Value ◽  
Semistructured Interviews ◽  
Social Media Platforms ◽  
Business To Consumer ◽  
Social Media Presence

This study’s purpose was to uncover national sport organizations’ (NSOs) perceptions of social media to understand how social media are situated and implemented. Specifically, the study sought to understand the perceived utility of social media, the rationale for the content produced and disseminated, and the factors affecting social-media implementation. Through semistructured interviews with Canadian NSOs, results were grouped into 3 themes: the value of social media (i.e., benefits, potential, and credibility), social-media use (i.e., content, types of social-media platforms, and rationale/motivations), and the challenges associated with social media (i.e., capacity, language issues, stakeholders engagement or lack thereof, and resistance). NSOs implement social media solely for business-to-consumer purposes. Social media act as a “double-edged sword”: NSOs believe that a good social-media presence requires sufficient resources but remain unconvinced of the “true” strategic value of social media.

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