Humanitarian aidHumanitarian aid is material and logistic assistance to people who need help. It is usually short-term help until the long-term help by the government and other institutions replaces it. Among the people in need are the homeless, refugees, and victims of natural disasters, wars, and famines. Humanitarian relief efforts are provided for humanitarian purposes and include natural disasters and human-made disasters. The primary objective of humanitarian aid is to save lives, alleviate suffering, and maintain human dignity.
Humanitarian principlesThere are a number of meanings for the term humanitarian. Here, humanitarian pertains to the practice of saving lives and alleviating suffering. It is usually related to emergency response (also called humanitarian response) whether in the case of a natural disaster or a man-made disaster such as war or other armed conflict. Humanitarian principles govern the way humanitarian response is carried out. Humanitarian principles are a set of principles that governs the way humanitarian response is carried out.
HumanitarianismHumanitarianism is an active belief in the value of human life, whereby humans practice benevolent treatment and provide assistance to other humans to reduce suffering and improve the conditions of humanity for moral, altruistic, and emotional reasons. One aspect involves voluntary emergency aid overlapping with human rights advocacy, actions taken by governments, development assistance, and domestic philanthropy.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Exploratory data analysisIn statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments.
Automated machine learningAutomated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge of applying machine learning. The high degree of automation in AutoML aims to allow non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning.
Social mediaSocial media are interactive technologies that facilitate the creation and sharing of information, ideas, interests, and other forms of expression through virtual communities and networks. While challenges to the definition of social media arise due to the variety of stand-alone and built-in social media services currently available, there are some common features: Social media are interactive Web 2.0 Internet-based applications.
Rule-based machine learningRule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learners that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.
TurkeyTurkey (Türkiye, ˈtyɾcije), officially the Republic of Türkiye (Türkiye Cumhuriyeti ˈtyɾcije dʒumˈhuːɾijeti), is a country located mainly on the Anatolian Peninsula in West Asia, with a small portion on the Balkan Peninsula in Southeast Europe. It borders the Black Sea to the north; Georgia to the northeast; Armenia, Azerbaijan, and Iran to the east; Iraq to the southeast; Syria and the Mediterranean Sea to the south; the Aegean Sea to the west; and Greece and Bulgaria to the northwest. Cyprus is off the south coast.
Social media marketingSocial media marketing is the use of social media platforms and websites to promote a product or service. Although the terms e-marketing and digital marketing are still dominant in academia, social media marketing is becoming more popular for both practitioners and researchers. Most social media platforms have built-in data analytics tools, enabling companies to track the progress, success, and engagement of ad campaigns.
DataIn common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.
Social networkA social network is a social structure made up of a set of social actors (such as individuals or organizations), sets of dyadic ties, and other social interactions between actors. The social network perspective provides a set of methods for analyzing the structure of whole social entities as well as a variety of theories explaining the patterns observed in these structures. The study of these structures uses social network analysis to identify local and global patterns, locate influential entities, and examine network dynamics.
Secularism in TurkeyIn Turkey, secularism or laicism (or laïcité) was first introduced with the 1928 amendment of the Constitution of 1924, which removed the provision declaring that the "Religion of the State is Islam", and with the later reforms of Turkey's first president Mustafa Kemal Atatürk, which set the administrative and political requirements to create a modern, democratic, secular state, aligned with Kemalism. Nine years after its introduction, laïcité was explicitly stated in the second article of the then Turkish constitution on February 5, 1937.
DisinformationDisinformation is false information deliberately spread to deceive people. It should not be confused with misinformation, which is false information but is not deliberate. "Fake news" has sometimes been categorized as a type of disinformation, but scholars have advised not using these two terms interchangeably or using "fake news" altogether in academic writing since politicians have weaponized it to describe any unfavorable news coverage or information.
Online machine learningIn computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning is a common technique used in areas of machine learning where it is computationally infeasible to train over the entire dataset, requiring the need of out-of-core algorithms.
Armenians in TurkeyArmenians in Turkey (Türkiye Ermenileri; Թուրքահայեր, also Թրքահայեր, "Turkish Armenians"), one of the indigenous peoples of Turkey, have an estimated population of 50,000 to 70,000, down from a population of over 2 million Armenians between the years 1914 and 1921. Today, the overwhelming majority of Turkish Armenians are concentrated in Istanbul. They support their own newspapers, churches and schools, and the majority belong to the Armenian Apostolic faith and a minority of Armenians in Turkey belong to the Armenian Catholic Church or to the Armenian Evangelical Church.
Fake news websiteFake news websites (also referred to as hoax news websites) are websites on the Internet that deliberately publish fake news—hoaxes, propaganda, and disinformation purporting to be real news—often using social media to drive web traffic and amplify their effect. Unlike news satire, fake news websites deliberately seek to be perceived as legitimate and taken at face value, often for financial or political gain. Such sites have promoted political falsehoods in India, Germany, Indonesia and the Philippines, Sweden, Mexico, Myanmar, and the United States.
AccessibilityAccessibility is the design of products, devices, services, vehicles, or environments so as to be usable by people with disabilities. The concept of accessible design and practice of accessible development ensures both "direct access" (i.e. unassisted) and "indirect access" meaning compatibility with a person's assistive technology (for example, computer screen readers). Accessibility can be viewed as the "ability to access" and benefit from some system or entity.
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
