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Semantic Brand Score
The Semantic Brand Score (SBS) is a measure of brand importance that is calculated on textual data. The measure is rooted in graph theory and partly connected to Keller's conceptualization of brand equity. It is calculated by converting texts into word or semantic networks and analyzing three key aspects: the frequency with which a brand name is mentioned (prevalence), the extent to which it is linked to distinctive and uncommon terms in the discourse (diversity), and its potential role as a bridge that connects otherwise unconnected or weakly connected terms or concepts (connectivity). The metric has also been used more broadly as an indicator of semantic importance, with varying objectives, by examining different text sources, such as newspaper articles, online forums, scientific papers, or social media posts. Definition and calculation Pre-processing To compute the Semantic Brand Score, it is necessary to convert the analyzed texts into word networks, i.e., graphs where ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brand Importance
A brand is a name, term, design, symbol or any other feature that distinguishes one seller's goods or service from those of other sellers. Brands are used in business, marketing, and advertising for recognition and, importantly, to create and store value as brand equity for the object identified, to the benefit of the brand's customers, its owners and shareholders. Brand names are sometimes distinguished from Generic brand, generic or store brands. The practice of branding—in the original literal sense of marking by burning—is thought to have begun with the ancient Egyptians, who are known to have engaged in livestock branding and branded slaves as early as 2,700 BCE. Branding was used to differentiate one person's cattle from another's by means of a distinctive symbol burned into the animal's skin with a hot branding iron. If a person stole any of the cattle, anyone else who saw the symbol could deduce the actual owner. The term has been extended to mean a strategic person ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Betweenness Centrality
In 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, that is, there exists at least one path 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. Betweenness centrality was devised as a general measure of centrality: it applies to a wide range of problems in network theory, including problems related to social networks, biology, transport and scientific cooperation. Although earlier authors have intuitively described centrality as based on betweenness, gave the first formal definition of betweenness centrality. Betweenness centrality finds wide application in network theory; it represents the degree to which nodes stand between each other. For example, in a telecommunications network, a node with higher b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graph Algorithms
An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations. With the increasing automation of services, more and more decisions are being made by algorithms. Some general examples are; risk assessments, anticipatory policing, and pattern recognition technology. The following is a list of well-known algorithms. Automated planning Combinatorial algorithms General combinatorial algorithms * Brent's algorithm: finds a cycle in function value iterations using only two iterators * Floyd's cycle-finding algorithm: finds a cycle in function value iterations * Gale–Shapley algorithm: solves the stable matching problem * Pseudorandom number generators (uniformly dist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Mining
Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al. (2005), there are three perspectives of text mining: information extraction, data mining, and knowledge discovery in databases (KDD). Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output. 'High quality' in text mining usually ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Social Network Analysis
Social 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 proliferation, information circulation, friendship and acquaintance networks, business networks, knowledge networks, difficult working relationships, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through '' sociograms'' in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of inter ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Analytics
Semantic analytics, also termed ''semantic relatedness'', is the use of ontologies to analyze content in web resources. This field of research combines text analytics and Semantic Web technologies like RDF. Semantic analytics measures the relatedness of different ontological concepts. Some academic research groups that have active project in this area include Kno.e.sis Center at Wright State University among others. History An important milestone in the beginning of semantic analytics occurred in 1996, although the historical progression of these algorithms is largely subjective. In his seminal study publication, Philip Resnik established that computers have the capacity to emulate human judgement. Spanning the publications of multiple journals, improvements to the accuracy of general semantic analytic computations all claimed to revolutionize the field. However, the lack of a standard terminology throughout the late 1990s was the cause of much miscommunication. This prompted Bu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Network Theory
In mathematics, computer science, and network science, network theory is a part of graph theory. It defines networks as Graph (discrete mathematics), graphs where the vertices or edges possess attributes. Network theory analyses these networks over the symmetric relations or directed graph, 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. Applications of network theory include Logistics, logistical networks, the World Wide Web, Internet, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.; see List of network theory topics for more examples. Euler's solution of the Seven Bridges of Königsberg, Seven Bridges of Königsberg problem is c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graph Theory
In mathematics and computer science, graph theory is the study of ''graph (discrete mathematics), graphs'', which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of ''Vertex (graph theory), vertices'' (also called ''nodes'' or ''points'') which are connected by ''Glossary of graph theory terms#edge, edges'' (also called ''arcs'', ''links'' or ''lines''). A distinction is made between undirected graphs, where edges link two vertices symmetrically, and directed graphs, where edges link two vertices asymmetrically. Graphs are one of the principal objects of study in discrete mathematics. Definitions Definitions in graph theory vary. The following are some of the more basic ways of defining graphs and related mathematical structures. Graph In one restricted but very common sense of the term, a graph is an ordered pair G=(V,E) comprising: * V, a Set (mathematics), set of vertices (also called nodes or points); * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brand Valuation
Brand valuation is the process of estimating the total financial value of a brand. A conflict of interest exists if those who value a brand were also involved in its creation. The ISO 10668 standard specifies six key requirements for the process of valuing brands, which are transparency, validity, reliability, sufficiency, objectivity; and financial, behavioral, and legal parameters. Brand valuation is distinct from brand equity. Brand value Traditional marketing methods examine the price/value relationship in terms of dollars paid. Some marketers believe customers perceive the value to mean the lowest price. While this may be true for standardized commercial products, some branding techniques are moving beyond this evaluation. Brand valuation emerged in the 1980s. Early pioneers in brand valuations included the British branding agency, Interbrand, led by John Murphy and Michael Birkin, which is credited with leading the concept's development. Millward Brown was also a leadin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brand Management
In marketing, brand management refers to the process of controlling how a brand is perceived in the market (economics), market. Tangible elements of brand management include the look, price, and packaging of the product itself; intangible elements are the experiences that the target markets share with the brand, and the relationships they have with it. A brand manager oversees all aspects of the consumer's brand association as well as relationships with members of the supply chain. Developing a good relationship with target markets is essential for brand management. Definitions In 2001, Hislop defined branding as "the process of creating a relationship or a connection between a company's product and emotional perception of the customer for the purpose of generating segregation among competition and building loyalty among customers". In 2004 and 2008, Kapferer and Keller respectively defined it as a fulfillment in customer expectations and consistent customer satisfaction.Shamoon, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Brand Equity
Brand equity, in marketing, is the worth of a brand in and of itself – i.e., the social value of a well-known brand name. The owner of a well-known brand name can generate more revenue simply from brand recognition, as consumers perceive the products of well-known brands as better than those of lesser-known brands. In the research literature, brand equity has been studied from two different perspectives: cognitive psychology and information economics. According to cognitive psychology, brand equity lies in consumer's awareness of brand features and associations, which drive attribute perceptions. According to information economics, a strong brand name works as a credible signal of product quality for imperfectly informed buyers and generates price premiums as a form of Return on brand, return to branding investments. It has been empirically demonstrated that brand equity plays an important role in the determination of price structure and, in particular, firms are able to charge p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Big Data
Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data processing, data-processing application software, software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include Automatic identification and data capture, capturing data, Computer data storage, data storage, data analysis, search, Data sharing, sharing, Data transmission, transfer, Data visualization, visualization, Query language, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: ''volume'', ''variety'', and ''velocity''. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Thus a fourth concept, ''veracity,'' refers to the quality or insightfulness of the data. Without sufficient investm ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
