Probabilistic Models for Social Media Mining

2014 ◽  
pp. 95-105
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

Probabilistic Models for Social Media Mining

2011 ◽  
Vol 6 (1) ◽  
pp. 13-24 ◽  
Author(s):  
Flora S. Tsai
Keyword(s):  
Social Media ◽  
Real World ◽  
Probabilistic Models ◽  
The Other ◽  
Media Content ◽  
Real World Data ◽  
Social Media Mining ◽  
Additional Information ◽  
Classification Framework ◽  
Media Mining

This paper proposes probabilistic models for social media mining based on the multiple attributes of social media content, bloggers, and links. The authors present a unique social media classification framework that computes the normalized document-topic matrix. After comparing the results for social media classification on real-world data, the authors find that the model outperforms the other techniques in terms of overall precision and recall. The results demonstrate that additional information contained in social media attributes can improve classification and retrieval results.

scholarly journals SEARCHING FOR THE FORGOTTEN: EXAMINING THE ONLINE PRESENCE OF VICTIMS OF POLICE KILLINGS

2021 ◽  
Author(s):  
Jennifer Pierre ◽  
Morgan Currie ◽  
Britt Paris ◽  
Irene Pasquetto
Keyword(s):  
Social Media ◽  
Potential Role ◽  
Media Content ◽  
Social Media Data ◽  
Social Media Mining ◽  
Source Of Information ◽  
Media Data ◽  
Official Police ◽  
Media Mining

This paper examines the potential role of social media in enhancing the understanding and perception of victims of police killings and the data collection surrounding these incidents. Through a series of content analysis and social media mining exercises, the authors observe the emergence of three distinct types of social media content offered on victims of police killings: persistence of the deceased’s activity across social media, sensational commentary on videos and blog postings, and memorials on Facebook, Twitter, and Tumblr. As part of a larger investigation of the availability and accessibility of official police homicide data, this paper aims to present social media data as a potentially powerful source of information to supplement quantitative reports. This process may be especially useful for the most affected communities, particularly BIPOC communities.

scholarly journals Social media mining in drug development—fundamentals and use cases

2021 ◽  
Author(s):  
Jonathan Koss ◽  
Astrid Rheinlaender ◽  
Hubert Truebel ◽  
Sabine Bohnet-Joschko
Keyword(s):  
Social Media ◽  
Drug Development ◽  
Use Cases ◽  
Social Media Mining ◽  
Media Mining

SOCIAL MEDIA MINING SHARED TASK WORKSHOP

2015 ◽  
Author(s):  
ABEED SARKER ◽  
AZADEH NIKFARJAM ◽  
GRACIELA GONZALEZ
Keyword(s):  
Social Media ◽  
Shared Task ◽  
Social Media Mining ◽  
Media Mining

scholarly journals Análisis del hashtag #MeQuedoEnCasa: la conversación digital por twitter® ante la emergencia producida por la covid-19

2021 ◽  
Vol 26 (2) ◽  
pp. 375-394
Author(s):  
Cristina Vela Delfa ◽  
Lucia Cantamutto ◽  
Marian Núñez-Cansado
Keyword(s):  
Social Media ◽  
Redes Sociales ◽  
Social Media Mining ◽  
Media Mining

La crisis sanitaria de la covid-19 vino acompañada de medidas de aislamiento, entre las que se encontraba el confinamiento domiciliario, que provocaron múltiples reacciones en las redes sociales. El objetivo de este artículo consiste en analizar la conversación digital observada en Twitter®, en torno al hashtag #MeQuedoEnCasa, en el periodo comprendido entre el 20 y el 27 de marzo de 2020. El estudio parte de una metodología mixta, en la que se combinan técnicas de análisis del social media mining con estrategias cualitativas propias del análisis lingüístico. Desde el punto de vista teórico, nos apoyamos en conceptos de las teorías del encuadre y de la valoración. Los resultados apuntan al enmarque positivo del confinamiento, a través de rasgos semióticos de distinto nivel: léxico, semántico y pragmático. Las cuentas más influyentes inclinaron su producción discursiva hacia la polaridad positiva. El análisis empírico permite concluir que el encuadre discursivo de esta conversación digital combina dos ejes semánticos (colectividad y salud), dos ejes enunciativos (aquí y ahora) y un eje emocional, lo que implica que hashtags como #MeQuedoEnCasa funcionan como señas de identidad social, como marcas de anclaje enunciativo y como instrumentos para fomentar la responsabilidad del individuo desde valores positivos.

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