Digital Commons Network^™

Safety First Means Safety Fits- An Awareness Campaign For Inclusive Ppe Designed For Women, Reagan Kellen Tonda

Construction Management

The construction industry has long overlooked the unique needs of women in terms of personal protective equipment (PPE), leading to discomfort and safety risks. This paper presents the "Safety First Means Safety Fits" social media awareness campaign, which aims to increase awareness about the importance of size-inclusive PPE for women and the progress being made in the industry. The campaign utilized social media, specifically Instagram, as a platform for dialogue and information distribution. The campaign involved the creation of an Instagram account (@safetyfits_CP) and the development of six posts addressing various aspects of women's PPE. The posts were promoted through …

Evaluation Of Different Machine Learning, Deep Learning And Text Processing Techniques For Hate Speech Detection, Nabil Shawkat

MSU Graduate Theses

Social media has become a domain that involves a lot of hate speech. Some users feel entitled to engage in abusive conversations by sending abusive messages, tweets, or photos to other users. It is critical to detect hate speech and prevent innocent users from becoming victims. In this study, I explore the effectiveness and performance of various machine learning methods employing text processing techniques to create a robust system for hate speech identification. I assess the performance of Naïve Bayes, Support Vector Machines, Decision Trees, Random Forests, Logistic Regression, and K Nearest Neighbors using three distinct datasets sourced from social …

Like You Search, Gipson Bachman

LMU/LLS Theses and Dissertations

As consumers continue to make their purchases solely online without visiting brick-and-mortar stores, they increasingly look for ways to “touch, feel and try on” products without actually doing so. We believe social media influencers provide a way to do this, with the influencers themselves acting as “stand-ins” for consumers in their place. Finding influencers that look like you in 2022 sounds like it would be easy, but it isn’t. Until now.

LIKE YOU aims to answer this gap in the market by creating a proprietary search engine that, through answering a few questions, recommends a list of influencers that can …

Efficacy Of Social Media Analysis As A Service (Smas) For Crisis Events, Rohit Kumar Khattar

Theses and Dissertations

Social media data can be collected and analyzed during and after crisis events to aid in disaster relief efforts. Setting up a system to perform this analysis is associated with various technical challenges. This thesis presents the design and implementation of a social media analysis as a service system. This system is hosted on cloud infrastructure and allows for on demand collection, processing, and delivery of social media data via an intuitive web interface. The service model and cloud infrastructure allow the system to be highly scalable and produce near real time analysis data. A cost evaluation of the system …

Understanding Logistics Airmen’S Risk Information Seeking And Processing During The Covid-19 Pandemic: The Role Of Organizational Meetings In An Extended Prism Framework, Christopher T. Price

Theses and Dissertations

The purpose of this survey-based research was to understand how organizational workplace meetings surrounding the COVID-19 pandemic impacted logistics Airmen across the United States Air Force and subsequently played a role into their risk seeking behavior on social media. Specifically, this research tested an expanded Planned Information Risk Seeking Model with organizational meetings as an antecedent to determine if current meetings influenced an Airman's perceived behavioral control, attitude toward seeking, subjective norms, knowledge sufficiency an intentions to seek information regarding COVID-19.

Linking Social Media, Medical Literature, And Clinical Notes Using Deep Learning., Mohsen Asghari

Electronic Theses and Dissertations

Researchers analyze data, information, and knowledge through many sources, formats, and methods. The dominant data format includes text and images. In the healthcare industry, professionals generate a large quantity of unstructured data. The complexity of this data and the lack of computational power causes delays in analysis. However, with emerging deep learning algorithms and access to computational powers such as graphics processing unit (GPU) and tensor processing units (TPUs), processing text and images is becoming more accessible. Deep learning algorithms achieve remarkable results in natural language processing (NLP) and computer vision. In this study, we focus on NLP in the …

Social Media Based Algorithmic Clinical Decision Support Learning From Behavioral Predispositions, Radhika V. Medury

Doctoral Dissertations

Behavioral disorders are disabilities characterized by an individual’s mood, thinking, and social interactions. The commonality of behavioral disorders amongst the United States population has increased in the last few years, with an estimated 50% of all Americans diagnosed with a behavioral disorder at some point in their lifetime. AttentionDeficit/Hyperactivity Disorder is one such behavioral disorder that is a severe public health concern because of its high prevalence, incurable nature, significant impact on domestic life, and peer relationships. Symptomatically, in theory, ADHD is characterized by inattention, hyperactivity, and impulsivity. Access to providers who can offer diagnosis and treat the disorder varies …

Image Forgery Detection With Machine Learning, Lubna Alzamil

All Master's Theses

The issue of forged images is currently a global issue that spreads mainly via social networks. Image forgery has weakened Internet users’ confidence in digital images. In recent years, extensive research has been devoted to the development of new techniques to combat various image forgery attacks. Detecting fake images prevents counterfeit photos from being used to deceive or cause harm to others. In this thesis, we propose methods using the error level analysis algorithm to detect manipulated images. We show that our combination of image pre-processing and machine learning techniques is an efficient approach to detecting image forgery attacks.

Foster Care Support Foundation Volunteer And Capital Outreach Analysis, Abeer Bhatti, Alexandro Martinez, Sunny Patel, Desmond Vail

Senior Design Project For Engineers

Care Support Foundation (FCSF) provides free goods to children in Georgia. Annually, 11,000 volunteers are needed to deal with the massive influx of donations and fundraising events. Through our analyses, we aim to make recommendations to the FCSF, which can help raise funds and implement mitigating strategies that would increase funds and improve the foundation.

Data-Driven And Knowledge-Based Strategies For Realizing Crowd Wisdom On Social Media, Shreyansh Bhatt

Browse all Theses and Dissertations

The wisdom of the crowd is a well-known example of collective intelligence wherein an aggregated judgment of a group of individuals is superior to that of an individual. The aggregated judgment is surprisingly accurate for predicting the outcome of a range of tasks from geopolitical forecasting to the stock price prediction. Recent research has shown that participants' previous performance data contributes to the identification of a subset of participants that can collectively predict an accurate outcome. In the absence of such performance data, researchers have explored the role of human-perceived diversity, i.e., whether a human considers a crowd as a …

An Open Source Approach To Social Media Data Gathering, Anthony J. Kallhoff

Theses and Dissertations

Modern usage of social media affords the military intelligence and analytic communities novel approaches to gather information. However, the tools and resources to develop these methodologies are still maturing. Furthermore, current data acquisition tools are not available to the DoD for all social media platforms. This thesis addresses a small subset of this problem by developing an open source methodological approach to collect and manage data from a popular social media site that has previously been inaccessible to defense intelligence organizations. This approach was operationalized via the R package called instaExtract, and an exemplar analysis was performed to demonstrate its …

Content-Based Clustering And Visualization Of Social Media Text Messages, Sydney A. Barnard

Browse all Theses and Dissertations

Although Twitter has been around for more than ten years, crisis management agencies and first response personnel are not able to fully use the information this type of data provides during a crisis or natural disaster. This thesis addresses clustering and visualizing social media data by textual similarity, rather than by only time and location, as a tool for first responders. This thesis presents a tool that automatically clusters geotagged text data based on their content and displays the clusters and their locations on the map. It allows at-a-glance information to be displayed throughout the evolution of a crisis. For …

A Semantically Enhanced Approach To Identify Depression-Indicative Symptoms Using Twitter Data, Ankita Saxena

Browse all Theses and Dissertations

According to the World Health Organization, more than 300 million people suffer from Major Depressive Disorder (MDD) worldwide. PHQ-9 is used to screen and diagnose MDD clinically and identify its severity. With the unprecedented growth and enthusiastic acceptance of social media such as Twitter, a large number of people have come to share their feelings and emotions on it openly. Each tweet can indicate a user's opinion, thought or feeling. A tweet can also indicate multiple symptoms related to PHQ-9. Identifying PHQ-9 symptoms indicated by a tweet can provide crucial information about a user regarding his/her depression diagnosis. The current …

A Fuzzy Logic-Based Text Classification Method For Social Media, Keyuan Wu

Theses

Social media offer abundant information for studying people’s behaviors, emotions and opinions during the evolution of various rare events such as natural disasters. It is useful to analyze the correlation between social media and human-affected events. This study uses Hurricane Sandy 2012 related Twitter text data to conduct information extraction and text classification. Considering that the original data contains different topics, we need to find the data related to Hurricane Sandy. A fuzzy logic-based approach is introduced to solve the problem of text classification. Inputs used in the proposed fuzzy logic-based model are multiple useful features extracted from each Twitter’s …

Incorporating A New Class Of Uncertainty In Disaster Relief Logistics Planning, Emre Kirac

Graduate Theses and Dissertations

In recent years, there has been a growing interest among emergency managers in using Social data in disaster response planning. However, the trustworthiness and reliability of posted information are two of the most significant concerns, because much of the user-generated data is initially not verified. Therefore, a key tradeoff exists for emergency managers when considering whether to incorporate Social data in disaster planning efforts. By considering Social data, a larger number of needs can be identified in a shorter amount of time, potentially enabling a faster response and satisfying a class of demand that might not otherwise be discovered. However, …

Preprocessing Techniques To Support Event Detection Data Fusion On Social Media Data, Brandon T. Davis

Theses and Dissertations

This thesis focuses on collection and preprocessing of streaming social media feeds for metadata as well as the visual and textual information. Today, news media has been the main source of immediate news events, large and small. However, the information conveyed on these news sources is delayed due to the lack of proximity and general knowledge of the event. Such news have started relying on social media sources for initial knowledge of these events. Previous works focused on captured textual data from social media as a data source to detect events. This preprocessing framework postures to facilitate the data fusion …

Environmental Dynamics: A Compendium Of Rhetorical Application, Annalisa Perez

Open Access Theses & Dissertations

Technology, albeit exceedingly useful, has exponentially exacerbated the communications dilemma between the technical and the non-technical. Additionally, based on a current new understanding of the term environmental, it can no longer be fully defined by terms such as air, water, waste, or purification. Rather, the meaning of environmental has been globally transformed in several ways. The term environmental is encompassing an expansion of understanding and is further defined with words such as essence, perception, rapport and multi-dimensional spaces. This work, Environmental Dynamics: A Compendium of Rhetorical Application (EDC), provides a framework where communication can be enhanced in areas where communication …

Detecting, Modeling, And Predicting User Temporal Intention, Hany M. Salaheldeen

Computer Science Theses & Dissertations

The content of social media has grown exponentially in the recent years and its role has evolved from narrating life events to actually shaping them. Unfortunately, content posted and shared in social networks is vulnerable and prone to loss or change, rendering the context associated with it (a tweet, post, status, or others) meaningless. There is an inherent value in maintaining the consistency of such social records as in some cases they take over the task of being the first draft of history as collections of these social posts narrate the pulse of the street during historic events, protest, riots, …

Spatial And Temporal Patterns Of Geo-Tagged Tweets, Yue Li

Open Access Theses

With over 500 million current registered users and over 500 million tweets per day, Twitter has caught the attention of scientists in various disciplines. As Twitter allows users to send messages with location tags, a massive amount of valuable geo-social knowledge is embedded in tweets, which can provide useful implications for human geography, urban science, location-based service, targeted advertising, and social network studies. This thesis aims to determine the lifestyle patterns of college students by analyzing the spatial and temporal dynamics in their tweets. Geo-tagged tweets are collected over a period of six months for four US Midwestern college cites: …

Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma

UNLV Theses, Dissertations, Professional Papers, and Capstones

With enormous amount of linguistic data present on web, text analysis has become one of the major fields of interest today. This field includes sentiment analysis, information retrieval, text document classification, knowledge based modeling, content similarity measure, data clustering, words prediction/correction, decision making etc. Managing and processing such data has vital importance. The field being quite broad, our focus is mainly on transportation related social media(Twitter) data extraction, text categorization/classification which can be further sub-divided into concept discovery, word sense disambiguation and sentiment analysis to analyze performance of existing transportation system worldwide. Concept discovery is the method of extracting the …

Facilitating Information Retrieval In Social Media User Interfaces, Anthony Costello

Electronic Theses and Dissertations

As the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters) that are amorphous and prone to rapid changes. It can be difficult for an individual human to filter through and organize the large amounts of information that can …

Attitudes And Behaviors In Online Communities: Empirical Studies Of The Effects Of Social, Community, And Individual Characteristics, Richard Kumi

Graduate Theses and Dissertations

Online communities and communities of practice bring people together to promote and support shared goals and exchange information. Personal interactions are important to many of these communities and one of the important outcomes of personal interactions in online communities and communities of practice is user-generated content. The three essays in the current study examines behavior motivation in online communities and communities of practice to understand how Social and personal psychological factors, and user-generated influence attitudes, intentions and behaviors in online communities.

The first essay addresses two research questions. First, how does Social capital influence exchange and combination behaviors in online …

Shoutboard : A New Locative Social Network, Evan Havlisch, Ketan Kumar, Tovin Thomas

Computer Science and Engineering Senior Theses

This paper will illustrate the need for a better location based social network that utilizes the latest smartphone features. Over the course of this project, we created ShoutBoard. ShoutBoard is a way for people to share messages with the people geographically close by. We accomplish this by creating a system with a client-server architecture. The user will use the iPhone app or the website to interact with our server. The server will fetch messages that other users have posted and return them to the client. Within this document, we describe in detail the problem we wish to solve, the current …

Virtual Interactions With Real-Agents For Sustainable Natural Resource Management, Tyler Pierce

Electronic Theses and Dissertations

Common pool resource management systems are complex to manage due to the absence of a clear understanding of the effects of users’ behavioral characteristics. Non-cooperative decision making based on individual rationality (as opposed to group rationality) and a tendency to free ride due to lack of trust and information about other users’ behavior creates externalities and can lead to tragedy of the commons without intervention by a regulator. Nevertheless, even regulatory institutions often fail to sustain natural common pool resources in the absence of clear understanding of the responses of multiple heterogeneous decision makers to different regulation schemes. While modeling …