A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.

An ethnomedicinal survey of a Tashelhit-speaking community in the High Atlas, Morocco

Traditional knowledge about medicinal plants from a poorly studied region, the High Atlas in Morocco, is reported here for the first time; this permits consideration of efficacy and safety of current practices whilst highlighting species previously not known to have traditional medicinal use. Our study aims to document local medicinal plant knowledge among Tashelhit speaking communities through ethnobotanical survey, identifying preferred species and new medicinal plant citations and illuminating the relationship between emic and etic ailment classifications. Ethnobotanical data were collected using standard methods and with prior informed consent obtained before all interactions, data were characterized using descriptive indices and medicinal plants and healing strategies relevant to local livelihoods were identified. 151 vernacular names corresponding to 159 botanical species were found to be used to treat 36 folk ailments grouped in 14 biomedical use categories. Thirty-five (22%) are new medicinal plant records in Morocco, and 26 described as used for the first time anywhere. Fidelity levels (FL) revealed low specificity in plant use, particularly for the most commonly reported plants. Most plants are used in mixtures. Plant use is driven by local concepts of disease, including “hot” and “cold” classification and beliefs in supernatural forces. Local medicinal plant knowledge is rich in the High Atlas, where local populations still rely on medicinal plants for healthcare. We found experimental evidence of safe and effective use of medicinal plants in the High Atlas; but we highlight the use of eight poisonous species.