Suchergebnisse

This study explores how Kuwaitis use Twitter to communicate their attitudes towards women Parliamentary candidates (WCs) in a traditionally male-dominated society, and how these tweeted attitudes are thematically constructed, either negatively or positively. The study also explores how these attitudes differ according to gender and evolve quantitatively and qualitatively over subsequent elections. A total of 1744 tweets about all eight women candidates in 2013 posted for 40 days prior to the Kuwait Parliamentary Election were retrieved and analyzed. The tweets posted about the two women candidates of those eight who continued to run in 2016 and 2020 were also analyzed in terms of length, content, and themes. Gender significantly correlated with attitudes in the first election, but not in the subsequent two elections. Tweeted attitudes turned to be more elaborate, information-based, and longer over consecutive elections. The dominant positive theme was generic, whereas the dominant negative theme was specific, and candidate based. Women candidates were praised for acting like men, whereas they are mocked for looking like men.

This study applies the model of technology acceptance (TAM) to examine the factors that explain the adoption and intensity of use of Facebook, Twitter, Instagram and Snapchat among a sample of college students in Kuwait. The three constructs that represented the predictor variables are perceived ease of use (PEOU), perceived usefulness (PU) and social influence (SI). Structural equation modelling was applied to analyse the impact and covariance of TAM constructs. Gender was used as a control variable to explain the variance in using Snapchat and Instagram. An 18-item questionnaire was developed and administered to a sample of 919 students at Kuwait University. The results show that Facebook and Twitter were male-dominated, whereas Instagram and Snapchat were female-dominated in the sample. TAM constructs invariably affect the adoption and intensity of using social networking sites. The use of Facebook and Snapchat is significantly explained by PU and PEOU, while the use of Twitter and Instagram is predicted by PEOU. PEOU was the only construct that explained the variance in the use of Twitter. SI was strongly correlated with PEOU and PU.