Social Media Text Analytics

Beheshti, Amin; Ghodratnama, Samira; Elahi, Mehdi; Farhood, Helia

doi:10.1201/9781003260141-4

Cited by 1 publication

(2 citation statements)

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“…For example, they can use data from customers that have actually made purchases for their product as an algorithm to find potential customers that have similar behaviour as them [6], [8]. By filtering out potential customers, Apple will be able to save time from those who won't be making purchases on Apple products [3], [9].…”

Section: Resultsmentioning

confidence: 99%

“…This will increase the efficiency of online human resources to increase their sales by not wasting time on customers that are unlikely to purchase their product. Web and social media analytics are done so that the online marketing of Apple's business can be more effective [9]. Customer's behaviour, preferences can be easily captured by performing web and social media analytics.…”

Section: Proposed Solutionmentioning

confidence: 99%

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A Comprehensive Exploration of Text, Web, Social Media, and Geospatial Analytics for Informed Decision Making

Tenya

2024

IJITCSA

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Text Analytics is the process of turning unstructured text data into useful information for analysis, to gauge consumer opinions, feedback, and product evaluations. It also provides search functionality, entity modelling, and emotional analysis to enable fact-based decision making. Analysis of website visitor behaviour is done using Web Analytics. The number of websites and users on the internet is growing daily. It is the process of tracking website information that can help to improve the web application features and evaluate the behaviour of users. By performing social media analytics on social media for example twitter, Instagram, Facebook. Data such as likes, comments, shares and saves can be obtained and analyse to know how the society think about the product. Geospatial analysis is used to make visualizations that include maps, graphs, statistics that show data according to geographic location. This is important to be analysed as it tells which area or country has the highest product sold or lowest subscription of the service. To make the data much easier for human brain to analyses or to make a conclusion, data visualization design is the process of putting all data information collected into a visual context. For instance, graph or map. The main objectives of data visualization are to make it simpler or easier to spot the outliers and patterns trends in big data sets. There are a variety of clustering processes or techniques available to arrange the data efficiently to its related data. The clustering process that is used in data mining is presented in this work.

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