CentralityIn graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin.
Character encodingCharacter encoding is the process of assigning numbers to graphical characters, especially the written characters of human language, allowing them to be stored, transmitted, and transformed using digital computers. The numerical values that make up a character encoding are known as "code points" and collectively comprise a "code space", a "code page", or a "character map". Early character codes associated with the optical or electrical telegraph could only represent a subset of the characters used in written languages, sometimes restricted to upper case letters, numerals and some punctuation only.
Eigenvector centralityIn graph theory, eigenvector centrality (also called eigencentrality or prestige score) is a measure of the influence of a node in a network. Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes. A high eigenvector score means that a node is connected to many nodes who themselves have high scores. Google's PageRank and the Katz centrality are variants of the eigenvector centrality.
Katz centralityIn graph theory, the Katz centrality or alpha centrality of a node is a measure of centrality in a network. It was introduced by Leo Katz in 1953 and is used to measure the relative degree of influence of an actor (or node) within a social network. Unlike typical centrality measures which consider only the shortest path (the geodesic) between a pair of actors, Katz centrality measures influence by taking into account the total number of walks between a pair of actors. It is similar to Google's PageRank and to the eigenvector centrality.
Character (computing)In computer and machine-based telecommunications terminology, a character is a unit of information that roughly corresponds to a grapheme, grapheme-like unit, or symbol, such as in an alphabet or syllabary in the written form of a natural language. Examples of characters include letters, numerical digits, common punctuation marks (such as "." or "-"), and whitespace. The concept also includes control characters, which do not correspond to visible symbols but rather to instructions to format or process the text.
Social network analysisSocial network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, meme spread, information circulation, friendship and acquaintance networks, peer learner networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships.
Betweenness centralityIn graph theory, betweenness centrality is a measure of centrality in a graph based on shortest paths. For every pair of vertices in a connected graph, there exists at least one shortest path between the vertices such that either the number of edges that the path passes through (for unweighted graphs) or the sum of the weights of the edges (for weighted graphs) is minimized. The betweenness centrality for each vertex is the number of these shortest paths that pass through the vertex.
Dynamic network analysisDynamic network analysis (DNA) is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulation and multi-agent systems (MAS) within network science and network theory. Dynamic networks are a function of time (modeled as a subset of the real numbers) to a set of graphs; for each time point there is a graph. This is akin to the definition of dynamical systems, in which the function is from time to an ambient space, where instead of ambient space time is translated to relationships between pairs of vertices.
Character (arts)In fiction, a character is a person or other being in a narrative (such as a novel, play, radio or television series, music, film, or video game). The character may be entirely fictional or based on a real-life person, in which case the distinction of a "fictional" versus "real" character may be made. Derived from the Ancient Greek word χαρακτήρ, the English word dates from the Restoration, although it became widely used after its appearance in Tom Jones by Henry Fielding in 1749.
Network theoryIn mathematics, computer science and network science, network theory is a part of graph theory. It defines networks as graphs where the nodes or edges possess attributes. Network theory analyses these networks over the symmetric relations or asymmetric relations between their (discrete) components. Network theory has applications in many disciplines, including statistical physics, particle physics, computer science, electrical engineering, biology, archaeology, linguistics, economics, finance, operations research, climatology, ecology, public health, sociology, psychology, and neuroscience.
Network scienceNetwork science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology.
Control characterIn computing and telecommunication, a control character or non-printing character (NPC) is a code point in a character set that does not represent a written character or symbol. They are used as in-band signaling to cause effects other than the addition of a symbol to the text. All other characters are mainly graphic characters, also known as printing characters (or printable characters), except perhaps for "space" characters. In the ASCII standard there are 33 control characters, such as code 7, , which rings a terminal bell.
Historical fictionHistorical fiction is a literary genre in which the plot takes place in a setting related to the past events, but is fictional. Although the term is commonly used as a synonym for historical fiction literature, it can also be applied to other types of narrative, including theatre, opera, cinema, and television, as well as video games and graphic novels. An essential element of historical fiction is that it is set in the past and pays attention to the manners, social conditions and other details of the depicted period.
Whitespace characterIn computer programming, whitespace is any character or series of characters that represent horizontal or vertical space in typography. When rendered, a whitespace character does not correspond to a visible mark, but typically does occupy an area on a page. For example, the common whitespace symbol (also ASCII 32) represents a blank space punctuation character in text, used as a word divider in Western scripts. With many keyboard layouts, a whitespace character may be entered by pressing .
Genre fictionGenre fiction, also known as formula fiction or popular fiction, is a term used in the book-trade for fictional works written with the intent of fitting into a specific literary genre in order to appeal to readers and fans already familiar with that genre. A number of major literary figures have written genre fiction. John Banville publishes crime novels as Benjamin Black, and both Doris Lessing and Margaret Atwood have written science fiction.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Scale-free networkA scale-free network is a network whose degree distribution follows a power law, at least asymptotically. That is, the fraction P(k) of nodes in the network having k connections to other nodes goes for large values of k as where is a parameter whose value is typically in the range (wherein the second moment (scale parameter) of is infinite but the first moment is finite), although occasionally it may lie outside these bounds. The name "scale-free" means that some moments of the degree distribution are not defined, so that the network does not have a characteristic scale or "size".
NovelA novel is a relatively long work of narrative fiction, typically written in prose and published as a book. The English word to describe such a work derives from the novella for "new", "news", or "short story of something new", itself from the novella, a singular noun use of the neuter plural of novellus, diminutive of novus, meaning "new". According to Margaret Doody, the novel has "a continuous and comprehensive history of about two thousand years", with its origins in the Ancient Greek and Roman novel, in Chivalric romance, and in the tradition of the Italian Renaissance novella.
Gothic fictionGothic fiction, sometimes called Gothic horror (primarily in the 20th century), is a loose literary aesthetic of fear and haunting. The name refers to Gothic architecture of the European Middle Ages, which was characteristic of the settings of early Gothic novels. The first work to call itself Gothic was Horace Walpole's 1764 novel The Castle of Otranto, later subtitled "A Gothic Story". Subsequent 18th-century contributors included Clara Reeve, Ann Radcliffe, William Thomas Beckford, and Matthew Lewis.
Text corpusIn linguistics and natural language processing, a corpus (: corpora) or text corpus is a dataset, consisting of natively digital and older, digitalized, language resources, either annotated or unannotated. Annotated, they have been used in corpus linguistics for statistical hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. In search technology, a corpus is the collection of documents which is being searched.
