442 research outputs found

    Adopting microblogging solutions for interaction with government

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    Authorities in the People’s Republic of China communicate with citizens using an estimated 600,000 Sina Weibo microblogs. This study reports on a study of Chinese citizens’ adoption of microblogs to interact with the government. Adoption results from trust and peer pressure in smaller-network ties (densely knit, pervasive social networks surrounding individual citizens). Larger-network ties (trust in institutions at large, such as the Chinese Communist Party, executive organizations, the judicial system, the media, etc.) are not associated with the adoption of microblogging. Furthermore, higher levels of anxiety are correlated with lower levels of use intention, and this finding underlines the impact of the Chinese authority’s surveillance and control activities on the lives of individual Chinese citizens. Based on these findings, we outline a theory of why citizens use microblogs to interact with the government and suggest avenues for further research into microblogs, state–citizen communication patterns and technology adoption

    Online Crowds Opinion-Mining it to Analyze Current Trend: A Review

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    Online presence of the user has increased, there is a huge growth in the number of active users and thus the volume of data created on the online social networks is massive. Much are concentrating on the Internet Lingo. Notably most of the data on the social networking sites is made public which opens doors for companies, researchers and analyst to collect and analyze the data. We have huge volume of opinioned data available on the web we have to mine it so that we could get some interesting results out of it with could enhance the decision making process. In order to analyze the current scenario of what people are thinking focus is shifted towards opinion mining. This study presents a systematic literature review that contains a comprehensive overview of components of opinion mining, subjectivity of data, sources of opinion, the process and how does it let one analyze the current tendency of the online crowd in a particular context. Different perspectives from different authors regarding the above scenario have been presented. Research challenges and different applications that were developed with the motive opinion mining are also discussed

    Cybernationalism and cyberactivism in China

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    El nacionalismo en la era de Internet se está convirtiendo cada vez más en un factor esencial que influye en la agenda-setting de la sociedad china, así como en las relaciones de China con los países extranjeros, especialmente con Occidente. Para China, una mejor comprensión de la estructura teórica universal y de los patrones de comportamiento del nacionalismo facilitaría la articulación social general de esta tendencia y potenciaría su papel positivo en la agenda-setting social. Por otra parte, un estudio del cibernacionalismo chino basado en una perspectiva china en el mundo académico occidental es un intento de transculturación. Desde el punto de vista de las relaciones internacionales y la geopolítica actuales, que son bastante urgentes, este intento ayudaría a mejorar la compatibilidad de China con el actual orden mundial dominado por Occidente, a reducir la desinformación entre China y otros países y a sentar las bases culturales e ideológicas para otras colaboraciones internacionales. Teniendo en cuenta el estado actual de la investigación sobre el nacionalismo chino y la naturaleza participativa de las masas del cibernacionalismo, esta disertación se centra en el cibernacionalismo en las tres partes siguientes. El primero es un estudio de los orígenes históricos del cibernacionalismo chino. Esta sección incluye tanto una exploración del consenso social en la antigua China como un estudio de la influencia del nacionalismo en la historia china moderna. El estudio de los orígenes históricos no sólo nos muestra la secuencia cronológica de la experiencia del desarrollo y la evolución tanto del proto-nacionalismo como del nacionalismo en China, sino que también revela un impulso decisivo para las reivindicaciones y comportamientos actuales del cibernacionalismo. La segunda parte trata del proceso de formación y ascenso del cibernacionalismo desde el siglo XXI. El importante antecedente del paso del nacionalismo al cibernacionalismo es el proceso de informatización de la sociedad china. Una vez completado el estudio de la situación básica de la sociedad china de Internet, especialmente el estudio de los medios sociales como espacio público, podemos vincular Internet con el nacionalismo y examinar el nuevo desarrollo del nacionalismo en la era de la participación de masas. El objetivo final es conectar el proto-nacionalismo, el nacionalismo y el cibernacionalismo, y seguir construyendo una comprensión del cibernacionalismo que sea coherente tanto con los principios universales del nacionalismo como con el contexto chino. Por último, validamos los resultados derivados del estudio anterior a través de la realidad social, es decir, estudiando las prácticas de ciberactivismo del cibernacionalismo para juzgar su suficiencia general así como su validez. Llevaremos a cabo varios estudios de caso de natural language processing basados en big data para reproducir la lógica de comportamiento y el impacto real del ciberactivismo de la manera más cercana posible a la realidad de Internet, evitando al mismo tiempo los defectos de argumentación unilateral y de infrarrepresentación de los estudios de caso tradicionales.Nationalism in the Internet age is increasingly becoming an essential factor influencing agendasetting within Chinese society, as well as China’s relations with foreign countries, especially the West. For China, a better understanding of the universal theoretical structure and behavioral patterns of nationalism would facilitate the overall social articulation of this trend and enhance its positive role in social agenda setting. On the other hand, a study of Chinese cybernationalism based on a Chinese perspective in western academia is an attempt at transculturation. From the viewpoint of the current rather urgent international relations and geopolitics, such an attempt would help to enhance China’s compatibility with the current western-dominated world order, reduce misinformation between China and other countries, and lay the cultural and ideological groundwork for various other international collaborations. Considering the current state of Chinese nationalism research and the mass participatory nature of cybernationalism, this dissertation focuses on cybernationalism in the following three parts. The first is a study of the historical origins of Chinese cybernationalism. This section includes both an exploration of the social consensus in ancient China and a survey of the influence of nationalism in modern Chinese history. The historical origins study not only shows us the chronological sequence of experiencing the development and evolution of both proto-nationalism and nationalism in China, but also reveals a decisive impetus for the current claims and behaviors of cybernationalism. The second part deals with the process of formation and rise of cybernationalism since the 21st century. The important background for the move from nationalism to cybernationalism is the informatization process of Chinese society. After we have completed the study of the basic situation of Chinese Internet society, especially the study of social media as a public space, we can link the Internet with nationalism and examine the new development of nationalism in the era of mass participation. The ultimate goal is to connect the proto-nationalism, nationalism, cybernationalism, and furtherly construct an understanding of cybernationalism that is consistent with both the universal principles of nationalism and the Chinese context. Finally, we validate the results derived from the previous study through social reality, i.e., by studying the cyberactivism practices of cybernationalism to judge its general sufficiency as well as validity. We will conduct several natural language processing case studies based on big data to reproduce the behavioral logic and actual impact of cyberactivism in the closest possible way to the Internet reality while avoiding the unilateral argumentation and under-representation flaws of traditional case studies

    A Pointillism Approach for Natural Language Processing of Social Media

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    Natural language processing tasks typically start with the basic unit of words, and then from words and their meanings a big picture is constructed about what the meanings of documents or other larger constructs are in terms of the topics discussed. Social media is very challenging for natural language processing because it challenges the notion of a word. Social media users regularly use words that are not in even the most comprehensive lexicons. These new words can be unknown named entities that have suddenly risen in prominence because of a current event, or they might be neologisms newly created to emphasize meaning or evade keyword filtering. Chinese social media is particularly challenging. The Chinese language poses challenges for natural language processing based on the unit of a word even for formal uses of the Chinese language, social media only makes word segmentation in Chinese even more difficult. Thus, even knowing what the boundaries of words are in a social media corpus is a difficult proposition. For these reasons, in this document I propose the Pointillism approach to natural language processing. In the pointillism approach, language is viewed as a time series, or sequence of points that represent the grams\u27 usage over time. Time is an important aspect of the Pointillism approach. Detailed timing information, such as timestamps of when posts were posted, contain correlations based on human patterns and current events. This timing information provides the necessary context to build words and phrases out of trigrams and then group those words and phrases into topical clusters. Rather than words that have individual meanings, the basic unit of the pointillism approach is trigrams of characters. These grams take on meaning in aggregate when they appear together in a way that is correlated over time. I anticipate that the pointillism approach can perform well in a variety of natural language processing tasks for many different languages, but in this document my focus is on trend analysis for Chinese microblogging. Microblog posts have a timestamp of when posts were posted, that is accurate to the minute or second (though, in this dissertation, I bin posts by the hour). To show that trigrams supplemented with frequency information do collect scattered information into meaningful pieces, I first use the pointillism approach to extract phrases. I conducted experiments on 4-character idioms, a set of 500 phrases that are longer than 3 characters taken from the Chinese-language version of Wiktionary, and also on Weibo\u27s hot keywords. My results show that when words and topics do have a meme-like trend, they can be reconstructed from only trigrams. For example, for 4-character idioms that appear at least 99 times in one day in my data, the unconstrained precision (that is, precision that allows for deviation from a lexicon when the result is just as correct as the lexicon version of the word or phrase) is 0.93. For longer words and phrases collected from Wiktionary, including neologisms, the unconstrained precision is 0.87. I consider these results to be very promising, because they suggest that it is feasible for a machine to reconstruct complex idioms, phrases, and neologisms with good precision without any notion of words. Next, I examine the potential of the pointillism approach for extracting topical trends from microblog posts that are related to environmental issues. Independent Component Analysis (ICA) is utilized to find the trigrams which have the same independent signal source, i.e., topics. Contrast this with probabilistic topic models, which leverage co-occurrence to classify the documents into the topics they have learned, so it is hard for it to extract topics in real-time. However, pointillism approach can extract trends in real-time, whether those trends have been discussed before or not. This is more challenging because in phrase extraction, order information is used to narrow down the candidates, whereas for trend extraction only the frequency of the trigrams are considered. The proposed approach is compared against a state of the art topic extraction technique, Latent Dirichlet Allocation (LDA), on 9,147 labelled posts with timestamps. The experimental results show that the highest F1 score of the pointillism approach with ICA is 4% better than that of LDA. Thus, using the pointillism approach, the colorful and baroque uses of language that typify social media in challenging languages such as Chinese may in fact be accessible to machines. The thesis that my dissertation tests is this: For topic extraction for scenarios where no adequate lexicon is available, such as social media, the Pointillism approach uses timing information to out-perform traditional techniques that are based on co-occurrence
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